Systems and methods for assessing security risk

ABSTRACT

Systems and methods for providing identification tests. In some embodiments, a system and a method are provided for generating and serving to a user an animated challenge graphic comprising a challenge character set whose appearance may change over time. In some embodiments, marketing content may be incorporated into a challenge message for use in an identification test. The marketing content may be accompanied by randomly selected content to increase a level of security of the identification test. In some embodiments, a challenge message for use in an identification test may be provided based on information regarding a transaction for which the identification test is administered. For example, the transaction information may include a user identifier such as an IP address. In some embodiments, identification test results may be tracked and analyzed to identify a pattern of behavior associated with a user identifier. A score indicative of a level of trustworthiness may be computed for the user identifier.

PRIORITY APPLICATIONS

This application is a continuation-in-part, and claims the benefit under35 U.S.C. §120, of U.S. patent application Ser. No. 12/935,927, filed onOct. 1, 2010, which was a National Stage of International ApplicationNo. PCT/IB2009/005645, filed on Mar. 31, 2009, which claims priorityunder 35 U.S.C. §119 to U.S. Provisional Application No. 61/041,556,filed on Apr. 1, 2008, and U.S. Provisional Application No. 61/050,839,filed on May 6, 2008. All of these applications are hereby incorporatedherein by reference in their entireties.

BACKGROUND OF INVENTION

The present disclosure relates generally to computer resource security.More particularly, the present disclosure relates to systems and methodsfor assessing security risk by analyzing user and/or transactioninformation.

Conventionally, an identification test is implemented by an entity incontrol of a computer resource to determine to what extent, if at all, auser should be granted access to the computer resource. For example, aweb site publisher may implement an identification test to authenticatea user, i.e., to determine whether the user is who he purports to be.Based on the outcome of the test, the publisher decides whether the useris authorized to access the requested resource (e.g., to view a webpage, to post a comment on a discussion forum and/or to perform atransaction via the web site).

This type of identification test is conventionally implemented as achallenge-response protocol executed between the publisher and the user.The publisher generates and serves to the user a challenge messagesoliciting a piece of information, such as an answer to a predeterminedsecurity question and/or a value derived based on a cryptographic secretknown only to an authentic user. The user must respond to the challengeby providing the solicited piece of information, and the publisherdetermines whether the user has passed the identification test byexamining the user's response.

The publisher may also implement an identification test to determine ifa user is a human user or a software robot (“bot”) programmed tosimulate a human user. This allows the publisher to restrict access bybots while continuing to provide access to humans, and is thereforedesirable in settings where bots pose a security threat. For example,the publisher may implement this type of identification test to preventbots from creating numerous new accounts and using the new accounts forillicit or nefarious purposes such as phishing, spoofing and/orspamming.

Some conventional identification tests for distinguishing between humanusers and bots incorporate static images into challenge messages to beserved to users. For example, in an image-based challenge called a“Completely Automated Public Turing Test to Tell Computers and HumansApart” (“captcha”), a static (graphic) image is presented in thechallenge message and the user is asked to respond based on the contentof the static image.

Several variants of static image captchas have been proposed, includingthe Gimpy, Bongo and Pix tests described below.

FIG. 1 shows an example of a Gimpy test, in which a word (e.g.,“trounce”) is selected from a dictionary and is displayed in a distortedand/or deformed fashion in a static image 102. The user is prompted toenter the displayed word in a text field 104 and is deemed to havepassed the test if the entered word matches the displayed word.

FIG. 2 shows an example of a Bongo test, in which a user is prompted tosolve a visual pattern recognition problem. In this example, thechallenge message contains a static image that shows, on the left-handside, symbols 202 drawn with relatively heavy line weights and, on theright-hand side, symbols 204 drawn with relatively-light line weights.The user is expected to recognize this pattern and respond by indicatingto which group (left or right) a separate symbol 206 belongs. As shownin FIG. 2, the user may indicate a group by clicking on one or morecheck boxes 208.

In a Pix test (not shown), several different static images are displayedto a user, and the user is prompted to name a subject common to all ofthe displayed images.

Sound-based captchas have also been proposed to accommodate visuallyimpaired users. For example, in an Eco test, a word or sequence ofnumbers is selected and rendered into a distorted sound clip. Uponplaying the sound clip, a user is prompted to enter the content of thesound clip and is deemed to have passed the test if the entered word ornumber sequence matches the actual content of the sound clip.

SUMMARY OF INVENTION

In some embodiments, a computer system is provided, for providing ananimated identification test for use in distinguishing human-generatedresponses from bot-generated responses. The computer system may compriseat least one processor programmed to generate and serve, via a computernetwork, to a user's browser a challenge graphic for display to the userby said browser, wherein the challenge graphic comprises a firstplurality of characters, and wherein an appearance of the firstplurality of characters changes over a time period during which thechallenge graphic is displayed.

In some embodiments, the computer system may further comprise aprocessor adapted to receive from the user a second plurality ofcharacters entered by the user in response to the challenge graphic,wherein said processor is further programmed to determine a result ofthe animated identification test at least partially by comparing thefirst plurality of characters and the second plurality of characters.

In some embodiments, the challenge graphic may comprise a feature thatat least partially obscures at least one first character of the firstplurality of characters during at least a portion of the time period.

In some embodiments, the first plurality of characters may comprise ananimated character whose appearance changes over the time period.

In some embodiments, the challenge graphic may comprise at least onemarketing feature adapted to convey a marketing message.

In some embodiments, the challenge graphic may further comprise at leastone other character that is not part of the first plurality ofcharacters.

In some embodiments, a computer-implemented method is provided, forproviding an animated identification test. The method may comprise: withat least one server, generating and serving to a user a challengegraphic, wherein the challenge graphic comprises a first plurality ofcharacters, and wherein an appearance of the first plurality ofcharacters changes over a time period during which the challenge graphicis displayed.

In some embodiments, at least one computer-readable medium is provided,encoded with a plurality of instructions that, when executed by at leastone processor, perform a method for providing an animated identificationtest. The method may comprise: with at least one server, generating andserving to a user a challenge graphic, wherein the challenge graphiccomprises a first plurality of characters, and wherein an appearance ofthe first plurality of characters changes over a time period duringwhich the challenge graphic is displayed.

In some embodiments, a computer-implemented method is provided, forproviding an identification test. The method may comprise: receiving ata server a request for an identification test to be administered to auser in connection with a transaction; operating a computer to provide achallenge message based at least in part on information regarding thetransaction, the challenge message comprising a first plurality ofcharacters to be displayed to the user; and receiving from the user inresponse to the challenge message a second plurality of characters,wherein a result of the identification test is determined at least inpart by comparing the first plurality of characters and the secondplurality of characters.

In some embodiments, at least one computer-readable medium is provided,encoded with a plurality of instructions that, when executed by at leastone processor, perform a method for providing an identification test.The method may comprise: receiving at a server a request for anidentification test to be administered to a user in connection with atransaction; operating a computer to provide a challenge message basedat least in part on information regarding the transaction, the challengemessage comprising a first plurality of characters to be displayed tothe user; and receiving from the user in response to the challengemessage a second plurality of characters, wherein a result of theidentification test is determined at least in part by comparing thefirst plurality of characters and the second plurality of characters.

In some embodiments, a computer system is provided, for providing ananimated identification test. The computer system may comprise: at leastone first communication interface adapted to receive a request for anidentification test to be administered to a user in connection with atransaction; at least one processor programmed to provide a challengemessage based at least in part on information regarding the transaction,the challenge message comprising a first plurality of characters to bedisplayed to the user; and at least one second communication interfaceadapted to receive from the user in response to the challenge message asecond plurality of characters, wherein a result of the identificationtest is determined at least in part by comparing the first plurality ofcharacters and the second plurality of characters.

In some embodiments, the at least one processor is further programmed todetermine a difference between the first plurality of characters and thesecond plurality of characters.

In some embodiments, the information regarding the transaction comprisesan identifier for the user.

In some embodiments, the information regarding the transaction comprisesinformation signifying a purpose of the identification test.

In some embodiments, the information regarding the transaction isprovided in the request for an identification test.

In some embodiments, the at least one first communication interface isfurther adapted to transmit a token message in response to the requestfor an identification test; the at least one process is furtherprogrammed to store first token information associated with the tokenmessage; and the at least one second communication interface is furtheradapted to receive from the user a data request comprising second tokeninformation associated with the token message, wherein the challengemessage is provided based at least in part on the first and second tokeninformation.

In some embodiments, the at least one processor is programmed to providea challenge message at least in part by determining a difficultycategory of the challenge message based at least in part on theinformation regarding the transaction.

In some embodiments, the at least one processor is programmed to providea challenge message at least in part by selecting a marketing messagebased at least in part on the information regarding the transaction.

In some embodiments, a computer-implemented method is provided, foranalyzing responses in animated identification tests. The method maycomprise: operating at least one first computer to monitor responses toa plurality of animated identification tests; associating each responsewith a same user identifier; measuring at least one characteristic ofthe responses to identify a pattern; and providing, based at least inpart on the identified pattern, score information in association withthe user identifier, the score information indicative of a level oftrustworthiness.

In some embodiments, at least one computer-readable medium is provided,encoded with a plurality of instructions that, when executed by at leastone processor, perform a method for analyzing responses in animatedidentification tests. The method may comprise: operating at least onefirst computer to monitor responses to a plurality of animatedidentification tests; associating each response with a same useridentifier; measuring at least one characteristic of the responses toidentify a pattern; and providing, based at least in part on theidentified pattern, score information in association with the useridentifier, the score information indicative of a level oftrustworthiness.

In some embodiments, a computer system is provided, for analyzingresponses in animated identification tests. The computer system maycomprise at least one processor programmed to: monitor responses to aplurality of animated identification tests; associate each response witha same user identifier; measure at least one characteristic of theresponses to identify a pattern; and provide, based at least in part onthe identified pattern, score information in association with the useridentifier, the score information indicative of a level oftrustworthiness.

In some embodiments, the at least one processor is further programmedto: store the score information in association with the user identifier;receive a request for an animated identification test; associate therequest for an animated identification test with the user identifier;and provide an animated identification test based at least in part onthe score information stored in association with the user identifier.

In some embodiments, the at least one characteristic comprises an amountof time between delivering a challenge message and receiving a responseto the challenge message.

In some embodiments, the responses are actual responses, and the atleast one characteristic comprises a difference between an actualresponse and a correct response.

In some embodiments, the at least one processor is further programmed tomonitor a rate at which requests for animated identification tests arereceived at the computer, the requests for animated identification testsbeing associated with the user identifier.

In some embodiments, the at least one processor is further programmed tomonitor a time of day at which a request for an animated identificationtest is received, the request for an animated identification test beingassociated with the user identifier.

In some embodiments, the at least one processor is further programmedto: determine, based at least in part on the responses to the pluralityof animated identification tests, that the user identifier is associatedwith a bot attack; and provide an updated assessment regarding at leastone of the plurality of animated identification test, the updatedassessment being different from an earlier assessment given to the atleast one of the plurality of animated identification test.

In some embodiments, the score information comprises informationindicative of a purpose of at least one of the plurality of animatedidentification tests.

In some embodiments, a computer-implemented method is provided, fordetermining an access privilege to be granted to a user to allow a userto access a computer resource. The method may comprise: operating atleast one first computer to determine a user identifier associated withthe user; with at least one second computer, receiving score informationassociated with the user identifier, the score information obtained atleast in part by analyzing a plurality of responses in past animatedidentification tests associated with the user identifier; and operatingat least one third computer to determine the access privilege to begranted to the user based at least in part on the score information.

In some embodiments, at least one computer-readable medium is provided,encoded with a plurality of instructions that, when executed by at leastone processor, perform a method for determining an access privilege tobe granted to a user to allow a user to access a computer resource. Themethod may comprise: operating at least one first computer to determinea user identifier associated with the user; with at least one secondcomputer, receiving score information associated with the useridentifier, the score information obtained at least in part by analyzinga plurality of responses in past animated identification testsassociated with the user identifier; and operating at least one thirdcomputer to determine the access privilege to be granted to the userbased at least in part on the score information.

In some embodiments, a computer system is provided, for determining anaccess privilege to be granted to a user to allow a user to access acomputer resource. The computer system may comprise: at least one firstprocessor programmed to determine a user identifier associated with theuser; at least one communication interface adapted to receive scoreinformation associated with the user identifier, the score informationobtained at least in part by analyzing a plurality of responses in pastanimated identification tests associated with the user identifier; andat least one second processor programmed to determine the accessprivilege to be granted to the user based at least in part on the scoreinformation.

In some embodiments, the at least one communication interface is furtheradapted to transmit a request for an animated identification test to beserved to the user; and the at least one second processor is furtherprogrammed to associate the request with the user identifier, whereinthe access privilege to be granted to the user is determined based atleast partially on a result of the animated identification test.

In some embodiments, a computer-implemented method is provided, forproviding an identification test. The method may comprise: at a server,receiving a request for an identification test; associating the requestwith a user identifier; retrieving from a computer-readable memorychallenge information associated with the user identifier; andgenerating, based at least in part on the challenge information, achallenge message to be served to a user, the challenge messagecomprising a first plurality of characters, wherein an appearance of thefirst plurality of characters changes over a time period during whichthe challenge message is served.

In some embodiments, at least one computer-readable medium is provided,encoded with a plurality of instructions that, when executed by at leastone processor, perform a method for providing an identification test.The method may comprise: at a server, receiving a request for anidentification test; associating the request with a user identifier;retrieving from a computer-readable memory challenge informationassociated with the user identifier; and generating, based at least inpart on the challenge information, a challenge message to be served to auser, the challenge message comprising a first plurality of characters,wherein an appearance of the first plurality of characters changes overa time period during which the challenge message is served.

In some embodiments, a computer system is provided, for providing anidentification test. The computer system may comprise: at least onecommunication interface adapted to receive a request for anidentification test; and at least one first processor programmed toassociate the request with a user identifier, retrieve from acomputer-readable memory challenge information associated with the useridentifier, and generate, based at least in part on the challengeinformation, a challenge message to be served to a user, the challengemessage comprising a first plurality of characters, wherein anappearance of the first plurality of characters changes over a timeperiod during which the challenge message is served.

In some embodiments, the computer system for providing an identificationtest may further comprise at least one second communication interfaceadapted to receive a second plurality of characters entered by the userin response to the challenge message; and at least one second processorprogrammed to determine a result of the identification test based, atleast partially, on the challenge information and the second pluralityof characters.

In some embodiments, a computer-implemented method is provided, forproviding a marketing service. The method may comprise: with at least afirst server, providing a web page to enable a first user to submitmarketing content; with at least a second server, generating and servingto a second user a challenge message for an identification test, whereinthe challenge message is generated based at least in part on marketingcontent received from the first user, and wherein the challenge messagecomprises a first plurality of characters; and receiving from the seconduser in response to the challenge message a second plurality ofcharacters, wherein a result of the identification test is determined atleast in part by comparing the first plurality of characters and thesecond plurality of characters.

In some embodiments, at least one computer-readable medium is provided,encoded with a plurality of instructions that, when executed by at leastone processor, perform a method for providing a marketing service. Themethod may comprise: with at least a first server, providing a web pageto enable a first user to submit marketing content; with at least asecond server, generating and serving to a second user a challengemessage for an identification test, wherein the challenge message isgenerated based at least in part on marketing content received from thefirst user, and wherein the challenge message comprises a firstplurality of characters; and receiving from the second user in responseto the challenge message a second plurality of characters, wherein aresult of the identification test is determined at least in part bycomparing the first plurality of characters and the second plurality ofcharacters.

In some embodiments, a computer system is provided, for providing amarketing service. The computer system may comprise: at least a firstserver adapted to provide a web page to enable a first user to submitmarketing content; at least a second server adapted to generate andserve to a second user a challenge message for an identification test,wherein the challenge message is generated based at least in part onmarketing content received from the first user, and wherein thechallenge message comprises a first plurality of characters; and atleast one communication interface adapted to receive from the seconduser in response to the challenge message a second plurality ofcharacters, wherein a result of the identification test is determined atleast in part by comparing the first plurality of characters and thesecond plurality of characters.

In some embodiments, the at least one communication interface is furtheradapted to receive from the second user a quality assessment of thechallenge message.

In some embodiments, a computer-implemented method is provided, forproviding an identification test. The method may comprise: with at leastone server, generating and serving to a user a challenge messagecomprising a first plurality of characters to be displayed to the user,wherein the first plurality of characters comprises a second pluralityof characters that is associated with marketing content promoting one ormore goods and/or services a second plurality of characters, and whereinthe first plurality of characters further comprises a third plurality ofcharacters that is selected randomly or pseudo-randomly; and receivingfrom the user in response to the challenge message a fourth plurality ofcharacters, wherein a result of the identification test is determined atleast in part by comparing the first plurality of characters and thefourth plurality of characters.

In some embodiments, at least one computer-readable medium is provided,encoded with a plurality of instructions that, when executed by at leastone processor, perform a method for providing an identification test.The method may comprise: with at least one server, generating andserving to a user a challenge message comprising a first plurality ofcharacters to be displayed to the user, wherein the first plurality ofcharacters comprises a second plurality of characters that is associatedwith marketing content promoting one or more goods and/or services asecond plurality of characters, and wherein the first plurality ofcharacters further comprises a third plurality of characters that isselected randomly or pseudo-randomly; and receiving from the user inresponse to the challenge message a fourth plurality of characters,wherein a result of the identification test is determined at least inpart by comparing the first plurality of characters and the fourthplurality of characters.

In some embodiments, a computer system is provided, for providing anidentification test. The computer system may comprise: at least oneserver adapted to generate and serve to a user a challenge messagecomprising a first plurality of characters to be displayed to the user,wherein the first plurality of characters comprises a second pluralityof characters that is associated with marketing content promoting one ormore goods and/or services a second plurality of characters, and whereinthe first plurality of characters further comprises a third plurality ofcharacters that is selected randomly or pseudo-randomly; and at leastone communication interface adapted to receive from the user in responseto the challenge message a fourth plurality of characters, wherein aresult of the identification test is determined at least in part bycomparing the first plurality of characters and the fourth plurality ofcharacters.

BRIEF DESCRIPTION OF DRAWINGS

In the drawings:

FIG. 1 shows an example of a Gimpy captcha image or message;

FIG. 2 shows an example of a Bongo captcha image or message;

FIG. 3 shows four different types of possible distortions that may beapplied to characters of a challenge character set of an identificationtest, in accordance with some embodiments of systems and methodsdiscussed herein;

FIG. 4A shows four frames of an illustrative identification testcaptured over a period of time, with a character overlapping feature inaccordance with some embodiments of systems and methods discussedherein;

FIG. 4B shows three frames of an illustrative identification testcaptured over a period of time, with a character overlapping feature inaccordance with some embodiments of systems and methods discussedherein;

FIG. 5 shows four frames of an illustrative identification test capturedover a period of time, with an additional character feature inaccordance with some embodiments of systems and methods discussedherein;

FIG. 6 shows four frames of an illustrative identification test capturedover a period of time, with a multiple frame feature in accordance withsome embodiments of systems and methods discussed herein;

FIG. 7A shows four frames of an illustrative identification testcaptured over a period of time, with a clutter feature in accordancewith some embodiments of systems and methods discussed herein;

FIGS. 7B and 7C each show three frames of an illustrative identificationtest captured over a period of time, with a clutter feature inaccordance with some embodiments of systems and methods discussedherein;

FIG. 8 shows four frames of an illustrative identification test capturedover a period of time, with a character obscuring feature in accordancewith some embodiments of systems and methods discussed herein;

FIG. 9 shows four frames of an illustrative identification test capturedover a period of time, with a transient character feature in accordancewith some embodiments of systems and methods discussed herein;

FIG. 10 shows an illustrative method for generating a frame of achallenge graphic, in accordance with some embodiments of systems andmethods discussed herein;

FIG. 11 shows an illustrative method for composing multiple images intoa single image, in accordance with some embodiments of systems andmethods discussed herein;

FIG. 12 shows an illustrative method for generating and/or manipulatingcharacter meshes, in accordance with some embodiments of systems andmethods discussed herein;

FIG. 13 shows an example of two character meshes, in accordance withsome embodiments of systems and methods discussed herein;

FIG. 14 shows examples of different warping effects (or, equivalently, asame effect varied over time) applied to the character meshes of FIG.13, in accordance with some embodiments of systems and methods discussedherein;

FIG. 15 illustrates an example of a third-party system for implementingidentification tests, in accordance with some embodiments of systems andmethods discussed herein;

FIG. 16 illustrates a first example of a protocol that may be executedcollectively by a user system, a publisher system and a third-partysystem, in accordance with some embodiments of systems and methodsdiscussed herein;

FIG. 17 illustrates a second example of a protocol that may be executedcollectively by a user system, a publisher system and a third-partysystem, in accordance with some embodiments of systems and methodsdiscussed herein;

FIG. 18 illustrates a third example of a protocol that may be executedcollectively by a user system, a publisher system and a third-partysystem, in accordance with some embodiments of systems and methodsdiscussed herein;

FIG. 19 illustrates an example of a third-party system comprisingvarious servers for performing various tasks in implementingidentification tests, in accordance with some embodiments of systems andmethods discussed herein;

FIG. 20 illustrates an example of a third-party system comprisingvarious server clusters for implementing identification tests, inaccordance with some embodiments of systems and methods discussedherein;

FIGS. 21A and 21B each show an illustrative configuration of anadvertisement matching service for use in implementing identificationtests, in accordance with some embodiments of systems and methodsdiscussed herein;

FIG. 22 shows an illustrative method for performing risk assessment, inaccordance with some embodiments of systems and methods discussedherein;

FIG. 23 illustrates an example of a risk assessment system comprisingvarious components for performing various tasks in risk assessment, inaccordance with some embodiments of systems and methods discussedherein; and

FIG. 24 is a schematic illustration of an exemplary computer or computersystem on which various aspects of the disclosed methods and systems maybe implemented.

DETAILED DESCRIPTION I. Overview

The inventor has appreciated that, as computers have become faster andsoftware and hardware more sophisticated, conventional identificationtests such as conventional captchas have become increasingly lesseffective in distinguishing between human users and bots. For example,bot programmers have developed sophisticated techniques for recognizingdistorted characters in Gimpy-style tests. However, conventionalattempts to thwart the ability of bots to solve identification testshave resulted in identification tests becoming more difficult for humanusers as well.

The inventor has recognized that, by contrast, animation may be employedin an image-based identification test to increase the level ofdifficulty for bots, without making the identification test excessivelydifficulty for humans. In some instances, the use of animation may evenenhance the ability of human users to solve the identification test(e.g., by making distorted, overlapping and/or partially obscuredcharacters easier for a human user to recognize).

The inventor has also appreciated that an animated identification testmay include much more information than a static identification test.Since the information is spread out over a period of time, a botattempting to solve an identification test may need to process much moreinformation than with a static identification test, and thereby consumemore resources. Consequently, a bot designer may be discouraged fromattempting to use a bot to access a web page employing an animatedidentification test.

Various systems and methods will now be presented, involving a number ofinventive aspects. Some embodiments will be discussed but theseembodiments are not intended to be exhaustive. The appended claimsdefine the invention with particularity and it is not the intention tohere in any way suggest the invention be understood in any way otherthan as defined in those claims. Indeed, it will be appreciated that theclaims define various aspects of the invention that may be practicedseparately or together, and that the claims cover embodiments that as ageneral rule may be practiced either independently or together, ascircumstances permit. Thus, there is no general intention thatembodiments are mutually exclusive though in some instances that may bethe situation. Further, the independent claims contain differentlimitations and different combinations of limitations. Accordingly, noreference to “the invention” or “the present invention” is intended torefer to all claimed subject matter.

In some aspects and embodiments, a system for implementing an animated(i.e., time-varying) identification test is provided, which includes asuitably programmed computer that generates and serves to a user achallenge graphic having a plurality of challenge characters that theuser is expected to identify in order to pass the identification test.The appearance of the plurality of challenge characters may change overa time period during which the challenge graphic is displayed. Asdiscussed in greater detail below, the change in appearance may beeffected in a number of different ways. For example, two challengecharacters may overlap each other in a time-varying manner (e.g., thedegree of overlap may become greater or smaller and/or the challengecharacters may overlap at different angles). This may increase thedifficulty for bots to segment and decode the individual challengecharacters. On the other hand, the time-varying nature of the overlapmay make it easier for human users to identify the challenge characters.

As another example, the plurality of challenge characters may bepartially obscured by one or more features incorporated into thechallenge graphic, where at least one feature is not part of theplurality of challenge characters. Such features, also referred to as“clutter” features, may comprise any combination of lines, curves, bars,blobs, symbols, any regular- or irregular-shaped objects, and evenadditional characters. As discussed in greater detail below, a manner inwhich the plurality of challenge characters is obscured by clutter mayvary in time, for example, by animating the plurality of challengecharacters and/or the clutter features, so that one or more the themmove, rotate, change size or undergo some other transformation(s).Again, the presence of clutter may make it more difficult for bots tosegment and decode individual challenge characters, while the relativemovement of the plurality of challenge characters and the clutterfeatures may help human users identify the challenge characters moreeasily.

The inventor has further recognized that three-dimensional (3D)rendering techniques may be used to generate challenge graphics foridentification tests. In some embodiments, a 3D mesh is created for oneor more challenge characters to be transcribed by a user in anidentification test and are manipulated to change the appearance of thechallenge characters. This technique may be used to produce many visualeffects, such as warping in any arbitrary manner, zooming in or out,and/or changing a view frustum. The inventor has appreciated that thesevisual effects may improve the effectiveness of the identification testsin distinguishing between bots and humans, because humans are naturallyadept at recognizing 3D shapes and objects, while the problem is mademore complex for bots.

It should be appreciated that the term “character” is not limited tocharacters in the English alphabet or the alphabet of any otherlanguage. Rather, “character” is used herein to refer broadly to anygraphical feature, such as a symbol, a letter, a number, a punctuationmark, an ideogram, a wingding character, an emoticon, a geometric form,an unrecognizable form (e.g., an “inkblot”) or even an image (e.g., animage of an animal or an object).

The inventor has further appreciated that conventional techniques forimplementing identification tests may be limited in a number of aspects.For example, identification tests are conventionally implemented on aper-transaction basis by individual publishers. There is no tracking orcorrelation of identification tests administered during differenttransactions (e.g., transactions associated with a same user during acertain time period), nor any form of dynamic feedback (e.g., selectinga more or less difficult identification test to be served to a userbased on history information accumulated for the user during earliertransactions). There is also no sharing or aggregation of identificationtest information across multiple publishers (e.g., total number of newaccounts opened by a same user with different publishers during acertain time period). As a result, valuable information regarding usersand their behaviors may not be recorded and utilized to the fullestextent possible.

It should be appreciated that the terms “user” and “publisher” are usedherein to refer broadly to any entity engaged in one or more electronictransactions. While in some embodiments a publisher is an entity thatrequests an identification test for access control purposes and a useris an entity to whom an identification test is administered, the presentdisclosure is not so limited. Also, the terms “access” or “access toresources,” as used herein, may refer broadly to any type of access,such as viewing a web page, posting a comment, performing a transaction,or even establishing a connection. In some embodiments, a server (suchas a web server) may be considered a resource, and an access to theserver may comprise any generic action performed on the server, forexample, connecting to the server, performing administrative actionsrelating to an account on the server and/or sending a message via theserver.

Additionally, the terms “computer” and “system” are used herein to referbroadly to any device or collection of devices having a programmedprocessor. Examples of a computer or a system may include desktopcomputers, laptop computers, mobile phones, and/or personal dataassistants (PDAs).

In some embodiments, systems and methods are provided for implementingand tracking identification tests. Such a system may include one or moreservers which administer an identification test to the user. In someembodiments, the one or more servers may be operated by a third-partyentity, and may administer the identification test at the request of apublisher and/or in cooperation with one or more systems run by thepublisher. However, it should be appreciated that a third-partystructure such as the one described above is not required.

In some embodiments, a system for implementing and trackingidentification tests is provided, which provides a challenge message toa user in an identification test based on information regarding atransaction in connection with which the identification test isadministered. The transaction information may include a user identifier(e.g., an IP address associated with the user), a purpose of theidentification test (e.g., loading a web page, opening a new account,and/or posting a message), and/or any other suitable information. Thesystem may select a challenge message with a desired attribute (e.g., adesired level of difficulty) based on the transaction information.

In some embodiments, a system for analyzing responses in identificationtests is provided, which monitors multiple identification testsassociated with a same user and measures at least one characteristic ofthe responses to identify a pattern of behaviors. Based on themeasurements and/or any identified patterns, the system may assign ascore to the user indicative of a level of trustworthiness (or someother suitable characteristics). The response characteristics measuredby the system may include a response time, a likelihood that anincorrect response is the result of human error (e.g., a typographicalor spelling error), a rate at which responses are received from the sameuser, times of day at which the responses are received, and/or any othersuitable characteristics.

In some embodiments, a score associated with a user may be used inselecting a challenge message to be served to the user in a subsequentidentification test. For example, a score may be indicative of a levelof perceived risk associated with a user and a more difficult challengemessage may be served to a user with a higher score (when the scoringrubric is that a higher score is correlated to higher perceived risk, ofcourse). Additionally, or alternatively, a score (or derived value) maybe provided to a publisher to enable the publisher to determine one ormore appropriate access privileges to be granted to the user. Forexample, the score may be used by the publisher in conjunction with aresult of an identification test to determine an appropriate accessprivilege.

It should be appreciated that a “score” need not be a numeric score andmay comprise any suitable performance characterization structured in anysuitable way. For example, it may contain raw measurements obtained fromuser responses and/or descriptions of behavioral patterns identified andcompiled by the system.

The inventor has recognized that identification tests may be utilized asa marketing vehicle. In some embodiments, a system is provided thatgenerates challenge graphics to be used in identification tests based onmarketing contents (e.g., marketing messages promoting one or more goodsand/or services). For example, marketing content may be incorporatedinto a challenge graphic as one or more graphical features and/ortextual messages. A user may be highly motivated to view the marketingcontent because it is delivered in the context of an identification testthat the user wishes to complete. Additionally, or alternatively, amarketing message may be included as part of a character string that auser must identify and transcribe in order to successfully complete theidentification test. This level of user focus and direct engagement maybe highly effective in reinforcing the marketing message in the user'smind.

The inventor has further appreciated that identification tests generatedbased on a relatively small collection of marketing contents may not besufficiently difficult for bots, because a bot may have a high successprobability by simply guessing a marketing message. In some embodiments,a web site may be provided to enable users to submit marketing contentto be incorporated in one or more identification tests to beadministered to other users, thereby increasing the diversity ofmarketing contents from which identification tests are generated.Additionally, or alternatively, randomly selected content may beincorporated into an identification test along with marketing content(e.g., by appending or otherwise inserting in a suitable manner one ormore randomly selected characters to a marketing message and requiring auser to transcribe both the marketing message and the randomly selectedcharacter(s)). Both of these techniques may reduce the likelihood that abot can successfully complete the identification tests by guessing.

It should be appreciated that “marketing content” is used herein torefer broadly to any content to be distributed, whether or not purposedto sell goods or services. Examples of marketing content include, butare not limited to, commercial advertisements for goods and/or services,political and/or non-political campaign messages, directions to a user(e.g., to activate a button), questions to a user (e.g., “What is 5+2?”or “What is the capital of Canada?”) and/or user-defined questions(e.g., security questions).

Some illustrative embodiments are described in greater detail below inconnection with FIGS. 3-24. However, it should be appreciated thatvarious inventive aspects may be used alone, in combination, or in avariety of arrangements not specifically discussed in the embodimentsdescribed herein, and that they are therefore not limited in theirapplications to the details and arrangements of components set forth inthe following description or illustrated in the drawings. For example,aspects described in connection with one embodiment may be combined inany manner with aspects described in other embodiments.

II. Examples of Challenge Graphics

FIGS. 3-9 illustrate examples of graphical features that may be includedin a challenge graphic of an identification test. These features may bestatic or animated, and may be positioned on static or animated imagesto form challenge graphics. In some embodiments, one or more animatedcomponents of a challenge graphic may be displayed in one or more timedloops that repeat one or more times until an event occurs, such as auser entering a response in one or more fields, a user logging off, orthe like.

In some embodiments, the graphical features may include two or morecharacters strung together to form a challenge character set that a useris expected to recognize and transcribe. Although not required, thechallenge character set may include one or more words or phrases. Thechallenge character set may additionally, or alternatively, include twoor more characters strung together to form one or more random ornonsensical groupings of characters.

In some embodiments, one or more security enhancing techniques may beapplied in generating a challenge graphic for an identification test.Some suitable techniques may include, for example, character distortion,character movement, addition of characters that are not part of achallenge character set, multiple layers of graphics, variableintermittent omission of selected characters, variable intermittentobscuring of selected characters, and transient characters. A suitablecombination of these techniques may result in an identification testthat is acceptably difficult for a bot to solve. In some embodiments, acombination of these techniques may result in an identification testthat is more difficult for a bot to solve than conventional captchas,but not more difficult for a human user to solve. In some embodiments, acombination of these techniques may even make an identification testless difficult for a human user to solve.

II.A. Character Distortion

FIG. 3 shows four different types of possible distortions that may beapplied to characters of a challenge character set of an identificationtest. In some embodiments, one or more characters may be arced, such asarced character groupings 302 showing respectively the character strings“Arcing 1,” “Arcing 2,” “Arcing 3” and “Arcing 4.” In some embodiments,one or more characters may be bulged (i.e., magnified in a distortedway), such as bulged character groupings 304 showing respectively thecharacter strings “Bulging 1” and “Bulging 2.” In some embodiments, oneor more characters may be wavy, such as waved character groupings 306showing respectively the character strings “The Wave 1” and “The Wave2.” In some embodiments, one or more characters may be twisted, such astwisted character groupings 308 showing respectively the characterstrings “Twist 1” and “Twist 2.”.

It should be appreciated that these four types of distortions are merelyexamples, as other types of distortions may also be suitable.Additionally, one or more different types of distortions may be appliedconcurrently to the same characters, to different characters, or toportions of the same characters. For example, a given distortion mayfade into non-distortion, or to another type of distortion along thelength of a character, along a string of one or more charactergroupings, or along an entire challenge character set.

In some embodiments, the application of one or more security enhancingtechniques other than distortion may be employed. Such techniques may,but need not, also lessen the amount of distortion needed to fend offbot attacks, which may make an identification test easier for a humanuser to solve. For example, one or more of the following types ofcharacter movements may be applied:

-   -   1) one or more characters may move within an image over time;    -   2) one or more characters may move together;    -   3) each character may move independently in the same direction,        or in a different direction, as one or more other characters,        with a similar or a different type of movement;    -   4) movements of one or more characters may follow one or more        patterns or may be random in velocity, direction, and/or        duration over a given period of time;    -   5) one or more of the characters may change orientation over        time (e.g., by rotating, swiveling, rocking, and/or flipping);    -   6) portions of one or more characters may internally move while        either remaining in a constant position in an image or while        moving about an image;    -   7) one or more characters (or portions of one or more        characters) may throb, pulsate, beat, undulate, flap, shake,        wag, flutter, pulse, pound, vibrate, expand, contract, flicker,        rattle, and/or roll; and    -   8) the distances between adjacent characters may increase or        decrease.

II.B. Character Overlap

In some embodiments, character overlap may be used as a securityenhancing technique. FIG. 4A shows four frames (Frame 1-Frame 4) of anillustrative identification test captured over a period of time, each ofthe frames including a same string of characters that forms a challengecharacter set 402. In this example, the challenge character set 402includes individual characters that overlap one another in atime-varying manner. For example, in Frame 1, the character “p” overlapsthe character “1” both at an upper portion and at a lower portion of thecharacter “1,” while in Frame 2, the character “p” overlaps thecharacter “1” only at an upper portion of the character “1.” Continuingto Frame 3, the character “p” does not overlap the character “1” at all,while in Frame 4 the character “p” overlaps the character “1” only at alower portion of the character “1.”

As shown in the example of FIG. 4A, characters in the challengecharacter set 402 may overlap one another in such a way that the amountand/or the location of an overlap may vary over time. Additionally, thechallenge character set 402 may include characters that rock back andforth or undergo other transformations. For example, the characters mayrock back and forth individually or collectively. As an another example,the characters may rock back and forth about multiple axes.

FIG. 4B shows three frames (Frame 1-Frame 3) of another illustrativechallenge graphic captured over a period of time, each frame includingthe same characters 404 (“A”) and 406 (“B”). In this example, theappearance of each of the characters 404 and 406 changes over time. Forexample, the characters 404 and 406 may each rotate in a differentdirection and/or at a different rate, so that an angle at which thecharacters 404 overlap each other may also vary over time. For example,as shown in FIG. 4B, the character 404 rotates clockwise from Frame 1 toFrame 3, while the character 406 rotates counterclockwise from Frame 1to Frame 3. As a result, the character 404 overlaps the character 406 ata lower portion of the character 406 in Frame 1, but at an upper portionof the character 406 in Frame 3.

II.C. Additional Characters

In some embodiments, a security enhancing technique may includedisplaying one or more additional characters that are not part of achallenge character set. FIG. 5 shows four frames of an illustrativeidentification test captured over a period of time, in which some of theframes include an additional character(s) 504 (e.g., “W”) that is notpart of a challenge character set 502 (e.g., “Example”). When one ormore additional characters, such as the additional character “W” 504, isor are added to a frame, different techniques may be applied to aid ahuman user in distinguishing between the additional characters from thechallenge character set. For example, the additional characters maydiffer from the challenge character set in one or more aspects,including appearance, movement, and/or duration of time displayed.

II.D. Multiple Layers of Animation

In some embodiments, multiple layers of animation may be used toimplement different types of movements within a challenge graphic. Forexample, multiple layers of animation may be incorporated into achallenge character set. FIG. 6 shows four frames of an illustrativeidentification test captured over a period of time, each frame includingmultiple layers of characters moving independently from one another. Inthis example, the challenge character set “EXAMPLE!” is divided intofour layers 602-605, each including a portion of the challenge characterset. Each of the layers 602-605 may move independently from the others.Additionally, characters within at least one of the layers 602-605 maydiffer in appearance from at least one other of the layers 602-605,and/or two or more of the layers 602-605 may move in concert for all, ora portion, of the duration of time in which the challenge graphic isdisplayed.

As another example, characters in a challenge graphic (e.g., charactersin the challenge character set and/or additional characters as discussedabove) may be divided into multiple groups in any suitable manner. Eachgroup may correspond to a different layer and may include differentvisual effects. In some embodiments, the groups of characters maypulsate, fade in and out, or otherwise appear and disappear in differentframes of animation in a complementary manner. For example, a challengecharacter set may comprise a word “test,” divided into two groups, suchas “te” (group 1) and “st” (group 2). Additional characters “abcd” mayalso be included and divided into, for example, two groups, “ab” (group3) and “cd” (group 4). These groups may be animated in such a way thatone or more groups may be visible while one or more other groups may beinvisible in a frame. For example, at a given instant, groups 1 and 4may be visible and groups 2 and 3 may be invisible. Visibility of thegroups may vary smoothly over time, e.g., by fading in and out, orabruptly. Thus, invisibility may be a matter of degree, rather than anabsolute condition. Additionally, visibility of the different groups mayvary over time in a coordinated manner, so that some groups may becomevisible as some other groups become invisible.

Of course, the transformations discussed above are not exhaustive, butare only illustrative.

II.E. Clutter

In some embodiments, a challenge graphic may include one or moregraphical features other than the challenge character set. Thesegraphical features may be incorporated into the background and/orforeground of the challenge graphic. Alternatively, or additionally,these graphical features may be layered above and/or below at least aportion of a challenge character set to at least partially obscure theportion of the challenge character set. Such graphical features areherein referred to, generally, as “clutter.”

FIG. 7A shows four frames of an illustrative identification testcaptured over a period of time, each frame including a layer of clutteranimation 702 overlaid onto a challenge character set 704. In thisexample, the layer of clutter animation 702 includes a substantiallyhorizontal line that vertically bifurcates the challenge character set704. This may make it more difficult for a bot to segment and decodeindividual characters in the challenge character set.

FIG. 7B shows three frames of another illustrative identification testcaptured over a period of time, each frame including a layer of clutteranimation 706 overlaid onto a character 708 (e.g., “A”). In thisexample, the layer of clutter animation 706 includes a bar moving acrossdifferent portions of the character 708. The bar may move in differentdirections over time, and/or it may have changing shapes and/ororientation. These and similar techniques may make it more difficult fora bot to decode the character 708.

In addition to a line or a bar, other suitable features may also be usedas clutter, such as blobs, symbols, any regular- or irregular-shapedfigures, and even additional characters or character strings that arenot part of a challenge character set (e.g., randomly selectedcharacters, randomly selected words, and/or a suitable combinationthereof). These features may be incorporated into one or more layers ofanimation overlaid onto a challenge character set. Also, clutter neednot be animated, and static clutter may also be used in addition to, orin conjunction with, animated clutter.

FIG. 7C shows three frames of an illustrative identification testcaptured over a period of time, each frame including a layer of clutter712 overlaid on a challenge character set 710 (e.g., “example”). In thisexample, a meaningful word is used in the challenge character set and astring of random characters is used as clutter, which may aid a humanuser in distinguishing the clutter from the challenge character setbecause a human user may be naturally drawn to the meaningful word inthe challenge character set. Additionally, the clutter characters may beanimated independently from the challenge character set, which mayfurther assist a human user in distinguishing the clutter from thechallenge character set. The human user may naturally recognizedifferent patterns of motion and use the differences as hints fordistinguishing between the clutter and the challenge character set. Bycontrast, it may be more difficult for a bot to perform a similarseparation.

In some embodiments, clutter characters may be rendered so that they aremore readily recognizable by a bot compared to characters in a challengecharacter set. This technique may increase the likelihood that a botdetects a clutter character and includes the detected clutter characterin a response to an identification test. Therefore, accurate botdetection may be achieved by looking for any character in the responsethat is part of one or more clutter features but not part of thechallenge character set. That is, a user may be determined to be a botif a response returned by the user contains a character that is onlyfound in clutter.

II.F. Variable Intermittent Omission/Obscuring of Selected Characters

In some embodiments, some of the characters of a challenge character setmay be omitted and/or obscured in one or more frames duringadministration of an identification test. For example, at any given timeduring an identification test, one or more characters of the challengecharacter set may be at least partially absent (e.g., disappearing orfading out), or at least partially obscured by one or more layers ofstatic or animated graphics. The static or animated (i.e., moving and/ortime-varying) graphics may take many different forms, such as a straightor curved bar, a block, a geometric figure, an irregular-shaped figure,and/or a character. A suitable combinations of these forms may also beused. Additionally, one or more features beneath one or more charactersmay move, appear, or disappear, to create one or more empty spaces wherecharacters used to be.

FIG. 8 shows four frames of an illustrative identification test capturedover a period of time, each frame including a challenge character set802. In each frame, at least one of the characters of the challengecharacter set 802 is at least partially obscured by a moving bar 804layered above or below the challenge character set 802.

In some embodiments, the appearance of one or more characters of thechallenge character set 802 may change while being at least partiallyobscured by the moving bar 804. For example, one or more characters ofthe challenge character set 802 may be distorted in different manners,move in different directions, and/or change orientation, while being atleast partially obscured by the moving bar 804.

It should be appreciated that any number of layers of graphics (e.g.,two or more moving bars) may be layered above and/or below the challengecharacter set 802. In some embodiments, the additional graphics may belayered above or below, or even in between, layers that form thechallenge character set 802. For example, each character in thechallenge character set 802 may correspond to a different layer and theadditional graphics may be layered between at least some of thedifferent layers. These additional graphics may be used to selectivelyblock or obscure certain layers of the challenge character set 802,without blocking or obscuring other layers.

II.G. Transient Characters

In some embodiments, one or more transient characters may appear in achallenge graphic for a duration of time that is shorter than theduration of an identification test. FIG. 9 shows four frames of anillustrative identification test captured over a period of time, each ofthe frames including a challenge character set 902 partially obscured bya moving bar 904. One of the frames includes a transient character 906(e.g., “F”) overlaid onto the moving bar 904 in line with the challengecharacter set 902.

In some embodiments, the transient character 906 may appear for aduration of time that is shorter than the duration of time for whichcharacters of the challenge character set 902 are displayed. Forexample, the transient character 906 may appear for a duration of timethat is long enough for a software robot to recognize, but not longenough for a human user to recognize. Additionally, or alternatively,the transient character 906 may be visually distinct from the challengecharacter set 902 due to timing, appearance, and/or location on thechallenge graphic. These properties may enable a human user to recognizethat the transient character 906 is not part of the challenge characterset 902. However, it may be difficult for bots to distinguish thetransient character 906 from characters in the challenge character set902. As a result, the presence of the transient character 906 in aresponse may be an indication that the response has been generated by abot, rather than a human user.

III. Techniques for Generating Challenge Graphics

Some illustrative techniques for generating challenge graphics foridentification tests are discussed below in connection with FIGS. 10-14.One or more of these techniques may be implemented on one or morecomputers to generate challenge graphics such as those shown in FIGS.3-9. In some embodiments, a challenge graphic generated using one ormore of these techniques may be delivered via a web page and/ordisplayed by a web browser (e.g., as part of an identification test).However, it should be appreciated that these techniques are merelyexemplary, and other techniques or combinations of techniques may alsobe suitable.

In some embodiments, an animated challenge graphic may include a seriesof frames, each of which may be generated by composing one or morelayers of graphics. A static challenge graphic may be considered aspecial case of an animated challenge graphic, i.e., one that consistsof only one frame (or multiple identical frames). An illustrative methodfor generating a frame is shown in FIG. 10.

In the embodiment shown in FIG. 10, individual layers of graphics aredivided into one or more groups, and all of the layers within each groupare rendered into a single image corresponding to the group. The groupsthus obtained may then be composed to obtain a single frame. Thisgrouping technique may enable application of certain blending techniquesto entire groups of layers, for example, to enhance the quality ofchallenge graphics. However, it is not required that the individuallayers be divided into groups. For example, the individual layers may berendered directly into a frame, without being divided into groups.

In act 1010, one or more individual layers of graphics are obtained inone or more suitable manners. For example, some layers may be retrievedfrom a computer-readable data storage and loaded into computer memory,while other layers may be created dynamically. As discussed above, eachlayer of graphics may be static or animated, and may include anysuitable combination of characters and/or non-character features.Illustrative methods for generating individual layers are discussed ingreater detail below in connection with FIGS. 12-14.

In act 1020, each individual layer obtained in act 1010 is rendered toan image. Any suitable rendering techniques may be employed to renderlayers to images, such as those provided by the Open Graphics Library(OpenGL).

In act 1030, an image is created for each group by composing a groupfrom the images obtained in act 1020 for the individual layers. Anillustrative method for composing images is shown in FIG. 11, althoughother suitable methods may also be used.

In act 1040, the images obtained in act 1030 corresponding respectivelyto the different groups are composed to form a single image, which maybe used as a frame in a challenge graphic. Again, any suitable methodfor composing images may be used, such as the one illustrated in FIG.11.

In the embodiment shown in FIG. 11, the images to be composed arearranged in a desired order (e.g., back-to-front). In act 1110, acurrent image is initialized, for example, by creating or loading adefault image. The default image may have a single pre-defined color(e.g., black). In act 1120, a next highest image to be composed isselected and, in act 1130, the selected next highest image is composedinto the current image to form a new current image. Then, in act 1140,it is determined whether at least one more image is to be composed intothe current image. If yes, the process returns to act 1120 to select anew next highest image, otherwise, the process ends and the currentimage is returned as the result of the composition.

The inventor has appreciated that, in some embodiments, it may bedesirable to provide challenge graphics that are of higher visualquality than in conventional identification tests. This may bedesirable, for example, where identification tests are used as amarketing vehicle by incorporating marketing contents into challengegraphics.

In some embodiments, challenge graphics of high visual quality may begenerated by applying various blending techniques as multiple images arecomposed to form a single image (e.g., when individual layers arecomposed into a group in act 1030 of FIG. 10 and/or when groups arecomposed into a frame in act 1040 of FIG. 10). For example, a top image(e.g., a next highest image as discussed in connection with FIG. 10) maybe composed into a background image (e.g., a current image as discussedin connection with FIG. 10) with transparency and translucency. Othermore complex techniques may also be used, such as using a top image as amask to modify a background image (e.g., to darken or lighten thebackground image). As another example, lighting information may beapplied to a top image to achieve shadowing effects in a backgroundimage as a result of the composition. This technique may be employed toimprove efficiency of the rendering process, by removing the need toinject shadow geometry and to render shadows fully in 3D.

These and many other techniques may be employed to improve the visualquality of challenge graphics. However, it should be appreciated thatsuch techniques are merely illustrative and are not required.

In some embodiments, each layer is modeled as a mesh, which is a list ofvertices and surfaces that represent a complex shape. A mesh may bedescribed in two dimensions (2D), three dimensions (3D), or even higherdimensions. In some embodiments, meshes are employed to allow forincreased diversity in the rendering of a frame. For example, a layermodeled as a 3D mesh may have variable depth (e.g., some features in thelayer may appear deeper into the scene than other features).

FIG. 12 shows an illustrative method by which a mesh corresponding toone layer may be generated. In act 1210, one or more individual meshesmay be obtained in one or more suitable manners. For example, when usedherein, a mesh may be generated dynamically and/or algorithmically, orit may be retrieved from a data storage and loaded into memory. In someembodiments, a mesh corresponding to one or more characters may begenerated dynamically based on a two-dimensional (2D) image of the oneor more characters in a 2D font. Optionally, the 2D image may bemanipulated using conventional techniques before it is used to generatea mesh. FIG. 13 shows an example of two character meshes, 1300A and1300B, each generated based on a 2D font. Although not show, a meshcorresponding to one or more characters may alternatively be generatedbased on a suitable representation of the characters in a 3D font.

Returning to FIG. 12, any number of the individual meshes obtained inact 1210 may be manipulated in act 1220. Manipulations of meshes may beperformed manually, algorithmically, and/or by applying one or morestored transformations that may or may not be time-varying.Additionally, different individual meshes may be manipulated using thesame or different techniques, some of which may be designed to make itmore difficult for a bot to recognize characters in a challengecharacter set of an identification test. FIG. 14 shows some examples ofcharacter meshes 1400A-L, obtained by manipulating the character meshes1300A and 1300B shown in FIG. 13 to achieve different warping effects.

Returning again to FIG. 12, the individual meshes, after they have beenmanipulated in act 1220, are merged into an aggregate mesh in act 1230.The process of merging may include determining the orientation of eachfeature represented by an individual mesh and/or the relative positionsof features represented by different individual meshes. The resultingaggregate mesh may be used as a finished model of a layer, or it may befurther manipulated in act 1240 to obtain a finished model of a layer.

It should be appreciated that the mesh-based techniques described aboveare merely exemplary. Other techniques may also be used for modeling,manipulating, and/or rendering a challenge graphic, instead of, or inaddition to, mesh-based techniques. For example, a particle system maybe used. A particle system may be particularly useful for creatingcertain visual effects (e.g., explosions, fire, water droplets, and/orsparks). Additionally, when a particle system is used, meshes may begenerated dynamically as particles are created or destroyed (e.g., on aframe-by-frame basis).

IV. Incorporating Content Into Identification Tests

Conventionally, identification tests are implemented for securitypurposes, for example, for distinguishing access requests originatingfrom human users from those originating from bots. To increase security,conventional identification tests such as some conventional captchas usecontents that are either randomly generated or randomly selected from alarge pool of pre-existing contents, such as books.

The inventor has appreciated that identification tests may beimplemented in many different ways and for many different purposes,other than those conventionally envisioned. For example, identificationtests may be used as a means of distributing user-generated content. Insome embodiments, a web site may be provided to enable web users tosubmit content to be incorporated into an identification test. Thecontent may be of any suitable format, such as a textual message, astatic image, a video clip, and/or an audio clip. Also, the content maybe distributed for any suitable purpose, for example, as part of apolitical or non-political public campaign or for marketing goods orservices.

The term “marketing content” is used herein to refer generally to anycontent to be distributed, regardless of the nature of the content.Examples of marketing content include advertisements relating to one ormore products and/or services offered by a sponsoring entity, which maypay a fee in exchange for the delivery of the advertisements viaidentification tests. However, it should be appreciated that paymentsmay not be required, and that if payments are required for at least someusers, any suitable payment structure may be imposed.

Marketing content may be incorporated into an identification test in anumber of different ways, including those discussed below. For example,graphical marketing content, which may or may not include characters,may be incorporated as one or more features in one or more layers in achallenge graphic of an identification test. Examples of graphicalmarketing content include logos, product images and/or any messagesembodied in images. The graphical marketing content, as well as thelayers into which it is incorporated, may each be static or animated.When animated, the graphical marketing content may appear, disappear, orotherwise change in appearance in any suitable way during theadministration of an identification test. Additionally, graphicalmarketing content may be used as clutter features which, as discussedabove, partially obscure a challenge character set to make it moredifficult for a bot to recognize the challenge character set. Forexample, the substantially horizontal line that vertically bifurcatesthe challenge character set shown in FIG. 7A may be replaced by a chainof logos and/or product images.

As another example, textual marketing content may be incorporated into achallenge character set of an identification test. The textual contentmay include any message such as a product or service name, a product orservice description, a marketing slogan and/or any message that a userwishes to convey via identification tests. As discussed above,characters and/or words other than those of the message may also beincluded, to decrease the likelihood that a bot succeeds in theidentification test by guessing a marketing message. For example,randomly selected characters may be added to a marketing message “I lovecola” to obtain a challenge character set such as “I love cola z11k” or“I z11k love cola.” Alternatively, or additionally, randomly selectedwords (e.g., from a dictionary or some other suitable collection ofwords) may be added to the marketing message to obtain a challengecharacter set, such as “I love soda super,” or “I really love soda.”

As yet another example, audio marketing content may be incorporated inone or more audio signals associated with an identification test, todeliver any message that a user wishes to convey via identificationtests.

Marketing content to be incorporated into an identification test may beobtained in any suitable way. For example, it may be provided directlyby a user (who may or may not represent a sponsoring entity), or it maybe generated dynamically based on information provided by the user.Also, the same or related marketing content may be incorporated intomultiple different identification tests.

V. Storage and Selection of Identification Tests

In some embodiments, identification tests may be generated as they areneeded (e.g., when a user requests access to one or more resources). Inother embodiments, identification tests may be generated in advance andstored in a data storage. This latter approach may be beneficial when anidentification test includes sophisticated graphics that arecomputationally expensive to generate. That is, generating challengegraphics in advance may maximize processor usage by spreading thecomputation load consistently through at least a portion of a day.

The data storage for identification tests may be configured in a mannerthat facilitates efficient retrieval and/or other additionalfunctionalities. For example, the identification tests may be stored in“pools” or “buckets” according to one or more attributes, e.g., a levelof difficulty. Alternatively, or additionally, each identification testmay be stored in association with some suitable metadata, such as a daterange during which the identification test may be administered, amaximum number of times the identification test may be administered,and/or a marketing campaign to which the identification test belongs.

The data storage may also be reconfigured and/or updated dynamically.For example, an identification test may be moved from one bucket toanother, or even entirely removed from the data storage. These changesmay be made based on any relevant information, such as the age of theidentification test, the number of times the identification test hasbeen administered, feedback from users and/or sponsoring entities,and/or results of recently administered identification tests. Forexample, an identification test may be associated with an expiry date(e.g., the end of a promotional campaign), after which theidentification test is removed from the data storage. As anotherexample, an identification test may be removed or re-classified if it isdetermined to be easy for a bot to solve and/or difficult for a humanuser to solve. This information may be obtained in any suitable way, forexample, by analyzing results of past administrations of theidentification test.

When they are needed, identification tests may be retrieved from thedata storage in one or more suitable manners. In some embodiments, abucket of identification tests may be chosen based on some relevantinformation, and an identification test is selected at random from thechosen bucket. For example, identification tests may be organized intobuckets according to difficulty levels, and a suitable bucket may bechosen by specifying a desired level of difficulty. As another example,identification tests may be organized into buckets according tomarketing campaigns, and a suitable bucket may be chosen by specifying adesired marketing campaign. Alternatively, or additionally, anidentification test may be chosen by issuing a database query andmatching the query against the metadata of the identification tests.Such a database query may be generated in any suitable way using anysuitable combination of information.

In some embodiments, the selection of identification tests may depend ona service agreement between a sponsoring entity and an entity thatprovides the identification tests. For example, the service agreementmay specify a service tier corresponding to a frequency or range offrequencies at which identification tests associated with the sponsoringentity are to be administered. Different service tiers corresponding todifferent frequencies may be sponsored at different cost levels. Asanother example, a sponsoring entity may specify in the serviceagreement one or more classes of publishers and/or users, so thatidentification tests sponsored by the sponsoring entity are administeredonly during transactions involving the specified publishers and/orusers.

In some embodiments, the selection of identification tests may depend ona service agreement between a publisher that requests identificationtests and an entity that provides identification tests. A publisher mayrequest that one or more classes of identification tests not beadministered to users requesting access to the publisher's resources.Alternatively, or additionally, a publisher may request that one or moreclasses of identification tests be the only identification testsadministered to users requesting access to the publisher's resources.Other types of preferences may also be specified.

VI. Other Functionalities

In some embodiments, one or more measures may be taken to control thequality of the marketing contents incorporated into identificationtests. This may be beneficial when at least some of the marketingcontents are submitted through a web page with little or no moderation.For example, slogans that are believed to be obscene and/or offensivemay be removed from use as soon as they are discovered to be obsceneand/or offensive. This may be achieved by providing a user interfaceelement (e.g., an “OFFENSIVE” button) with the identification test toallow a user to identify potentially offensive marketing content.Additionally, the user may be provided with the option to receive asubstitute identification test.

In some embodiments, a user interface element (e.g., a “HARD TO READ”button) may be provided with an identification test to allow a user toidentify an identification test that the user finds too difficult tosolve. The user may also be provided with the option to receive asubstitute identification test that is less difficult.

Many other features may also be implemented to improve security, userexperience, marketing effectiveness and/or other service qualities.Below is a non-exhaustive list of exemplary features that may beimplemented in any suitable combination.

-   -   1) A user may be allowed to rank two or more marketing contents.    -   2) A mobile-specific identification test format for        advertisements may be employed for users of mobile devices.    -   3) One or more advertisements may pop-up upon (or subsequent to)        a successful response to an identification test.    -   4) A rewards program may be available to a user upon the        successful completion of a predetermined number of        identification tests.    -   5) An identification test may include an “AUDIO” button which a        user may activate to hear a correct or expected response.    -   6) An identification test may include a “TEXT MESSAGE” button        which a user may activate to receive a text message of a correct        response. A user may enter an identifier of an electronic        device, such as a mobile phone number, to which the text message        with the correct response may be sent.    -   7) The placement of a user response field may appear in various        locations around a challenge graphic of an identification test.    -   8) A user response field may appear for an amount of time that        is less than the full duration of the identification test.

VII. Examples of System Implementations

Conventionally, two types of system architectures, in-house andthird-party, have been used for implementing identification tests. In anin-house architecture, an identification test (e.g., a captcha) isgenerated, served, and validated in a single computer or system. Forexample, when a user attempts to load a web page from a publisher, theweb server of the publisher generates a captcha image, serves thecaptcha to the user, and validates the user's response. By contrast, ina third-party architecture, a publisher uses a third-party system togenerate identification tests to be served to users. In some instances,the third-party system is also used to validate responses received fromthe users.

The inventor has appreciated that conventional systems for implementingidentification tests (both in-house and third-party) may be limited inseveral aspects. For example, they implement identification tests on aper-transaction basis only. There is no tracking and/or correlation ofidentification tests administered during different transactions (e.g.,transactions associated with a same user throughout a certain timeperiod), nor any form of dynamic feedback (e.g., selecting a more orless difficult identification test to be served to a user based onhistory information accumulated for the user during earliertransactions). Additionally, there is no sharing or aggregating ofidentification test information across multiple publishers that eachoperate their own in-house identification test system. As a result,valuable information regarding users and their behaviors may not berecorded and utilized to the fullest extent possible. For example, a botattack may be more readily detectable by examining the total number ofnew accounts opened by the same user with multiple different publishersduring a certain time period. However, there are no conventionaltechniques for collecting this type of information.

In some embodiments, improved systems and methods are provided forimplementing identification tests to enable tracking of identificationtest information. Such an improved system may include one or moreservers which, in cooperation with one or more computer systems run by auser, administer an identification test to the user. Additionally, theone or more servers may be operated by a third-party entity, and mayadminister the identification test at the request of a publisher and/orin cooperation with one or more systems run by the publisher. However,it should be appreciated that a third-party architecture is notrequired, as any of the functionalities provided by a third-party systemmay alternatively be provided by an in-house system.

VII.A. Third-Party Architecture

FIG. 15 illustrates an example of a third-party system 1506 forimplementing identification tests in accordance with some embodiments.The third-party system 1506 may include one or more servers adapted tocommunicate with a publisher system 1504 and/or a user system 1502. Thepublisher system 1504 may include one or more servers adapted tocommunicate with the third-party system 1506 and to engage in one ormore transactions with the user system 1502. For example, the usersystem 1502 may initiate a transaction with the publisher system 1504 togain access to one or more resources (e.g., web pages and/or new emailaccounts) provided by the publisher system 1504.

In some embodiments, the user system 1502 may include one or morecomputers adapted to communicate with the publisher system 1504 and/orthe third-party system 1506. The one or more computers may be operatedby a human user and/or a bot.

FIG. 16 illustrates an example of a protocol that may be executedcollectively by a user system, a publisher system and a third-partysystem. In this example, a challenge graphic is requested and providedfor use in an image-based identification test. However, it should beappreciated that other types of identification tests may also beemployed. For instance, in some embodiments, a challenge audio may beprovided for use in a sound-based identification test.

In act 1610, the user system transmits to the publisher system a requestfor permission to perform an action, such as accessing one or moreresources. In response to the access request, the publisher system maydetermine that an identification test is to be administered to the userbefore the user may proceed with the action. In act 1620, the publishersystem submits to the third-party system a request for a challengegraphic for use in an identification test to be served to the user.

In act 1625, the third-party system selects a challenge graphic from apre-generated collection of challenge graphics (or, alternatively,generates a challenge message upon receiving the request for a challengegraphic in act 1620) and transmits the selected challenge graphic to thepublisher system in act 1630. Based on the received challenge graphic,the publisher system serves an identification test to the user in act1635. Upon receiving the identification test, the user system displaysthe challenge graphic in act 1640 via a suitable output device (e.g., amonitor or a screen of an electronic device) and receives a response inact 1645 via a suitable input device (e.g., a keyboard) from a humanuser. Alternatively, in some embodiments (e.g., where the userrepresents a bot), acts 1640 and 1645 may be replaced by an automatedanalysis of the challenge graphic that produces a response to theidentification test.

In act 1650, the user system submits the response to the publishersystem, which in turn forwards the response to the third-party system inact 1655. In act 1660, the third-party system evaluates the responseforwarded by the publisher system (e.g., to determine whether theresponse is valid) and provides an appropriate evaluation result to thepublisher system in act 1665. Based on the evaluation result, thepublisher system determines in act 1670 whether to grant or deny theuser's request to access the resources.

It should be appreciated that the sequence of communications shown inFIG. 16 may be modified and/or augmented in various ways. For example,additional information may be exchanged in various acts ofcommunications described above for one or more different purposes, suchas increasing security and/or enabling enhanced functionalities.Examples of enhanced functionalities may include tracking ofidentification test results and/or intelligent selection of challengegraphics.

VII.B. Token-Based Transaction

In some embodiments, the request for a challenge graphic submitted inact 1620 may be preceded by another round of communications, in which atoken (e.g., a small text file, such as a so-called “cookie”) associatedwith the present transaction is created by the third-party system andtransmitted to the publisher system. The token may be passed from thepublisher system to the user system, so that the user system (instead ofthe publisher system) may request a challenge graphic by submitting thetoken. This mechanism may ensure that challenge graphics are providedonly to a user to whom a publisher wishes to administer anidentification test.

Utilizing tokens may also enable early error detection. In someembodiments, an error may be detected when the publisher system requestsa token from the third-party system but receives no response. Thus, thepublisher system may determine that the third-party system isinoperative and may stop serving identification test requests to avoidthe risk of system overloading.

FIG. 17 shows an illustrative protocol that uses tokens to distributeinformation. As in the example of FIG. 16, the protocol of FIG. 17begins when a user initiates a transaction with a publisher (e.g., byrequesting access to one or more resources in act 1710). Upon receivingthe access request, the publisher system determines that anidentification test is to be administered to the user and submits atoken request to the third-party system in act 1712.

As discussed above, the token request may contain any suitablecombination of information that may be used in achieving any suitablefunctionality. For example, the token request may contain authenticationinformation, such as a signature generated using the publisher system'sprivate key, that allows the third-party system to ascertain that thetoken request has originated from a legitimate publisher. This mayprevent attackers from obtaining and analyzing a sufficiently largenumber of challenge graphics in advance. As another example, the tokenrequest may contain an identifier for the transaction initiated by theuser and/or information regarding the nature of the transaction (e.g.,loading a web page, posting a comment to a discussion board, and/oropening a new account). As discussed in greater detail below inconnection with FIGS. 22 and 23, this information may be used toestimate a level of risk associated with the transaction.

Below is a list of different types of information that may be includedin a token request. It should be appreciated that this list is merelyillustrative, as other types of information may also be included,instead of, or in addition to, the types listed below, and less than allof this information may be included. Additionally, all or parts of theinformation contained in the token request may be encrypted, forexample, using a secret key shared between the publisher system and thethird-party system, or using a public key of the third-party system.

-   -   1) TIME_TREQ: A timestamp of when the token request is created.        This may be used to prevent replay attacks (e.g., an attacker        intercepting a token request from a legitimate publisher and        submitting it at a later time to obtain a token illegitimately).        In some embodiments, the timestamp may also be used as part of a        time-out mechanism, where the third-party system responds only        to token requests issued relatively recently (e.g., within a        predetermined time period).    -   2) SKEY: A unique cryptographic key associated with the present        transaction. This may be a secret key generated according to a        symmetric key encryption algorithm and may be used to encrypt        some or all of the information exchanged between the publisher        and the third-party.    -   3) USERDATA: This may be any custom-defined data that the        publisher chooses to include in the token request. For example,        it may be an identifier for the user within the publisher's        internal systems.    -   4) SESID: A session identifier associated with the present        transactions. USERDATA, SESID and/or some other suitable        information may be used to identify the present transaction in        subsequent communications between the third-party system and the        publisher system. For example, the third-party system may notify        the publisher system at a later time that the transaction        associated with USERDATA and/or SSID has been determined to be        part of an attack.    -   5) URI: A universal resource identifier (URI) identifying a        resource that the user is attempting to access (e.g., a web page        that the user is attempting to load). As discussed in greater        detail below, this information may be used to select a suitable        challenge graphic.    -   6) TYPE: An indication of the type of resource that the user is        attempting to access (e.g., opening a new account and/or posting        a comment). This may be used to determine a level of risk        associated with the present transaction and/to select a suitable        challenge graphic.    -   7) KUSER: An indication of whether the user is known to the        publisher system and/or third-party system (e.g., whether the        user has an existing account and/or is logged in to the        publisher system). It should be appreciated that a known user        need not be a trusted user.    -   8) IP: An Internet Protocol (IP) address of the user. In case        the user system communicates with the publisher system via a        proxy server, this may be the IP address of the proxy server.    -   9) XF: An X-Forward address of the user. This may be the “true”        IP address of the user, as provided by a proxy server via which        the user system communicates with the publisher system. IP        and/or XF may be used as an identifier for the user by the        third-party system.    -   10) UA: A user agent of the user. This may be any information        regarding a computer program through which the user system        communicates with the publisher system and/or the third-party        system. For example, UA may include a name and version for a web        browser of the user.    -   11) RF: A referrer of the user. This may be any information        regarding the user's browsing history. For example, RF may        indicate a referring web site via which the user arrives at a        current web site.

In act 1714, the third-party system creates a token and returns it tothe publisher system in act 1716, along with any other suitableinformation. The token may be created in any suitable way and may beused by the third party for any suitable purpose. In some embodiments,the token may serve as a unique identifier for the present transactionwithin the third-party system. Alternatively, or additionally, the tokenmay be a collection of data that is decipherable only by the third-partysystem and may be used as a means of distributing information betweendifferent parts of the third-party system over an untrustedcommunication medium (e.g., via the publisher system and/or the usersystem). This may improve performance of the third-party system, forexample, by enabling a server of the third-party system to complete arelevant portion of a transaction without contacting any other server inthe third-party system. Additionally, the token may be replicated invarious stages of a transaction, which creates a “built-in” redundancythat may improve reliability of the third-party system. For example,even when a server fails within the third-party system, another servermay obtain from a token all information necessary for completing arelevant portion of a transaction.

Below is an illustrative list of different types of information that maybe included in a token. It should be appreciated that other types ofinformation may also be included, instead of, or in addition to, thetypes listed below. Additionally, as discussed above, all or parts ofthe information contained in the token may be encrypted so that it canbe accessed only by the third-party system.

-   -   1) TIME_TOKEN: A timestamp of when the token is created. The        timestamp may be used to determine whether the token has expired        (i.e., whether the token has existed for more than a        predetermined period of time). In some embodiments, a token is        submitted with a request for a challenge graphic and a challenge        graphic is provided only if the token has not expired.    -   2) SKEY: This may be the cryptographic key provided by the        publisher system in the token request and may be used to encrypt        parts or all of the information exchanged between the publisher        system and the third-party system.    -   3) IP: An IP address of the user, as provided in the token        request by the publisher system. This may be used by the        third-party system to ascertain that a request for a challenge        graphic indeed originates from the same user to whom the        publisher intends to administer an identification test. For        example, in some embodiments, a token is submitted with a        request for a challenge graphic, and a challenge graphic is        provided only if the request for a challenge graphic originates        from the same IP address as specified in the token.    -   4) BID: An identifier for a bucket of challenge graphics from        which a challenge graphic is to be retrieved and served to the        user in the present transaction.    -   5) BIX: An index into the bucket BID, identifying a challenge        graphic to be retrieved and served to the user in the present        transaction.    -   6) RISK: An indication of the level and/or nature of the risk        associated with the present transaction or user. This may be        determined based on the IP address of the user, the type of the        resource that the user is attempting to access, and/or any other        suitable information. RISK may be used by various parts of the        third-party system to influence the present transaction. For        example, RISK may be used in selecting BID and/or BIX, which may        correspond to a more or less difficult challenge graphic and/or        a challenge graphic with clutter features that are more or less        visible to bots than to human users. As another example, RISK        may indicate a bandwidth requirement associated with the present        transaction and may be used to determine an amount of data        compression to be applied to a challenge graphic.

In addition to the token, a token response may contain other informationthat the third-party system wishes to convey to the publisher and/or theuser. Again, all or parts of the information contained in the tokenresponse may be encrypted so that it is accessible only to one or moreintended parties. Examples of information that may be contained in atoken response include:

-   -   1) VSERV: An identifier for a validation server within the        third-party system that may be used to validate a user response        in the present transaction. VSERV may comprise an address (e.g.,        an IP address and/or a URI) at which the publisher system may        connect to the validation server.    -   2) TRUST: An indication of a level of trust associated with the        user, as determined by the third-party system using, for        example, history information associated with the user. TRUST may        be a numerical value, or any other custom-defined value.    -   3) WIDGET: HTML and/or JavaScript code or the like for        displaying a challenge graphic.    -   4) SKIN: Data that may be used to customize the appearance        and/or functionality of a player for displaying a challenge        graphic. A player defines graphical content to be displayed        along with the challenge graphic, such as additional controls        (e.g., a refresh button for requesting a different challenge        graphic) and/or a box around a video screen that displays the        challenge graphic. The skin may be used to configure the player        so that the player has a desired “look and feel” in accordance        with a marketing campaign and/or a publisher's web site. The        skin may be written as an XML data structure, for example.    -   5) DSERV: An identifier for a data server within the third-party        system from which a challenge graphic may be requested. DSERV        may comprise an address at which the publisher system and/or        user system may connect to the data server.

Some or all of the information described above may be encrypted usingSKEY (i.e., the cryptographic key provided by the publisher system inthe token request) or some other suitable cryptographic key. Forexample, VSERV and TRUST may be encrypted using SKEY, while SKIN andDSERV may be unencrypted.

Upon receiving a token response from the third-party system, thepublisher system provides an identification test web page to the usersystem in act 1718. For example, the publisher system may transmit tothe user system HTML source having a widget for administering anidentification test (e.g., for displaying a challenge graphic and/orreceiving a user response). In some embodiments, the widget may specifyfailover behaviors to ensure that the challenge graphic is displayedproperly regardless of web browser settings. Below is an illustrativepseudo code segment for a widget.

If (JavaScript enabled) If (Flash enabled) DisplayFlashPlayer( ) ElseDisplayJavascriptPlayer( ) Else DisplayVideo( )

In this embodiment, if both JavaScript is enabled and an appropriateversion of Flash is installed, then DisplayFlashPlayer( ) is invoked,which may construct a Flash player and display a challenge graphic in ahigh quality format, such as MP4. If JavaScript is enabled but Flash isnot available, then DisplayJavascriptPlayer( ) is invoked, which mayconstruct a JavaScript player and display a challenge graphic in a lowerquality format, such as JPG animated through CSS (Cascading StyleSheets) Sprites. If JavaScript is not enabled, then DisplayVideo( ) isinvoked, which may display a challenge graphic in animated GIF format,along with a text entry field constructed using standard HTML.

The information transmitted from the publisher system to the user systemin act 1718 may also include a URI for obtaining a challenge graphic. Inact 1720, the user system uses the URI to request a challenge graphic.As discussed above, the URI may identify a data server of thethird-party system to which the user system may connect. Additionally,the URI may include information that the data server may use to selectan appropriate challenge graphic. For example, the URI may include someor all of the information contained in the token or token request asdiscussed above. Additionally, the URI may specify a format in which thechallenge graphic is to be returned (e.g., MP4 or GIF), and/or a refreshcount indicating a number of times the user has activated a “refresh”button to request a different challenge graphic within the sametransaction.

In act 1725, the third-party system (e.g., a data server of thethird-party system) selects challenge graphic based on informationcontained in the URI and returns a challenge graphic to the user systemin act 1730 in an appropriate format (e.g., based on the user system'sweb browser settings, as discussed above). If a token is included aspart of the URI, the third-party system may check the validity of thetoken (e.g., by decrypting the token and/or verifying a timestamp)before returning a challenge graphic.

Additionally, the third-party system may modify the manner in which thechallenge graphic is returned using any suitable combination ofinformation relating to the present transaction. In some embodiments,risk information (e.g. a RISK value as described above) is included in atoken that is passed first from a token server of the third-party systemto the publisher system in act 1716, then from the publisher system tothe user system in act 1718, and eventually from the user system to adata server of the third-party system in act 1720. This mechanism mayallow the data server of the third-party system to use the riskformation to determine how the challenge graphic is to be returned. Forexample, the challenge graphic may not be returned if the riskinformation indicates excessively high risk. Alternatively, thechallenge graphic may be returned in a fashion that may sufficientlyslow down a bot attack. For example, the challenge graphic may bereturned only after a suitable delay, or it may be streamed in a veryslow fashion.

In act 1740, the user system displays the challenge graphic received inact 1730 and receives a response in act 1745 from a human user. Forexample, the response may be a character string entered by the humanuser after viewing the challenge graphic. Alternatively, in someembodiments (e.g., where the user represents a bot), acts 1740 and 1745may be replaced by an automated analysis of the challenge graphic thatproduces a response to the identification test.

In act 1750, the user system submits the response to the publishersystem, which in turn forwards the response to the third-party system inact 1755 as part of a validation request. For example, the publishersystem may submit the validation request to a validation server of thethird-party system, as specified by the VSERV parameter in the tokenresponse transmitted to the publisher system in act 1716.

In addition to the response to be validated, the validation request maycontain any suitable information that may be used by the third-partysystem in evaluating the response, such as TIME_TREQ, SESID, IP, XF, UA,and/or RF, as discussed above. This information may enable thethird-party system to identify the present transaction and locate anexpected response against which the received response is compared.

Any other information from the token request of act 1710 and/or thetoken response of act 1716 may also be included in the validationrequest. For example, the token itself may be included, to enable avalidation server to make use of any risk information contained in thetoken (e.g., the RISK value as discussed above). In some embodiments,the expected response may be directly included in the token, so that thevalidation server may validate the received response without performingany lookups. Additionally, or alternatively, the token may includepublisher information, so that the validation server may check that thepublisher system issuing the validation request matches the publisherinformation contained in the token.

The third-party system evaluates a received response in act 1760. Insome embodiments, different modes of evaluation may be employeddepending on the value of RISK included in the token. For example, ifRISK indicates a high level of trust (or, equivalently, a low level ofrisk), some errors in the response may be tolerated. That is, a responsemay be deemed valid even though it may contain some discrepancies froman expected response. On the other hand, if RISK indicates a high levelof risk, then fewer or no errors may be tolerated. Some examples oferrors that might be tolerated are listed below.

-   -   1) Doubling of a character or a missing character. For example,        the actual response may be “spiice” or “spce,” where the        expected response is “spice.”    -   2) Substitution of a correct character by an incorrect character        that is located near the correct character on a keyboard. For        example, the actual response may be “spoce,” where the expected        response is “spice.”    -   3) Interchanging adjacent characters. For example, the actual        response may be “spcie,” where the expected response is “spice.”    -   4) Interchanging adjacent words in a sentence.    -   5) Other common typographical errors.

In act 1765, the third-party server provides an appropriate evaluationresult to the publisher system, which may contain any suitableinformation that the third-party system is programmed to convey to thepublisher. For example, in addition to an evaluation result, a timestampmay be provided so that the publisher system may determine whether thepresent transaction has timed out.

In some embodiments, a binary result (e.g., “Valid” or “Not Valid”) maybe provided to indicate whether the user has passed or failed theidentification test. In some other embodiments, the evaluation resultmay indicate an error has occurred and the identification test isinconclusive. An error code may also be provided to indicate the typeand/or source of the error.

Additionally, or alternatively, the evaluation result may indicate alevel of trust associated with the present transaction and/or with theuser. This information may be used by the publisher system to determinean appropriate access privilege to be granted to the user in act 1770.For example, the publisher system may determine to grant restrictedaccess when the trust level is low, even if the user passes theidentification test. Any form of restricted access may be imposed. Forexample, in an embodiment in which the user wishes to post a comment,the publisher system may decide to moderate the comment, or otherwiseinspect the comment using classification software such as a spam filter,before actually posting the comment.

It should be appreciated that the protocol described above in connectionwith FIG. 17 is merely illustrative, as other protocols may also besuitable. For example, the publisher system may push the overhead ofconnecting to the third-party system in act 1712 onto the user system.This may effectively distribute the workload relating to token requestsfrom a relatively small number of publisher systems to a much largernumber of user systems. FIG. 18 illustrates an example of a protocoladopting this strategy.

As in the example of FIG. 17, the protocol of FIG. 18 begins when a userinitiates a transaction with a publisher (e.g., by requesting access toone or more resources in act 1810). Upon receiving the access request,the publisher system determines that an identification test is to beadministered to the user and compiles a token request. Instead ofsubmitting the token request to the third-party system as in act 1712,the publisher system proceeds in act 1812 to provides an identificationtest web page to the user system, where the token request is transmittedalong with the HTML source. In some embodiments, the token request isencrypted using a public key of the third-party system or apre-established key shared between the publisher system and thethird-party system, and therefore security is not comprised bytransmitting the token request to the user system.

In act 1814, the user system forwards the token request to thethird-party system. In act 1816, the third-party system generates atoken (e.g., as in act 1714) and transmit the token response to the usersystem in act 1818. Acts 1820-1870 then proceeds in a fashion similar toacts 1720-1770.

While FIG. 18 illustrates an example in which the request for achallenge graphic (act 1820) is preceded by a token request (act 1814)and its associated response (act 1818), it should be appreciated thatthe use of a token is not required. For example, the protocol shown inFIG. 18 may be modified to exclude acts 1814, 1816 and 1818, so that theuser system proceeds directly to act 1820 to request a challenge graphicafter receiving an identification test web page in act 1812.

VII.C. Servers and Clusters

As discussed above, a third-party system may comprise one or moreservers for performing various functionalities. FIG. 19 illustrates anexample in which three servers, token server 1907, data server 1908 andvalidation server 1909, are used respectively for providing tokens,providing data (e.g., challenge graphics), and validating userresponses. As shown in FIG. 19, activities relating to providing tokens(e.g., acts 1712 and 1716 of FIG. 17) may take place via the tokenserver 1907, while those relating to providing data (e.g., acts 1720 and1730 of FIG. 17) may take place via the data server 1908 and thoserelating to response validation (e.g., acts 1755 and 1765 of FIG. 17)may take place via the validation server 1909.

It should be appreciated that servers may be merely logical entitiesdesignated for certain activities or combinations of activities. Tokenserver 1907, data server 1908 and validation server 1909 may in factreside on the same physical machine or on any combination of machinesrunning any combination of components. Additionally, the third partysystem may comprise servers other than token server 1907, data server1908 and validation server 1909.

In some embodiments, token server 1907 comprises a number of serverseach capable of receiving and responding to a token request. Similarlyfor data server 1908 and validation server 1909. These servers may beconfigured in any suitable manner. For example, they may be grouped intoclusters based on geographical proximity and/or functionality.

In some embodiments, the servers may be grouped into a collection ofToken-Data-Validation (TDV) clusters, where each cluster is capable ofreceiving and responding to token requests, data requests and validationrequests. FIG. 20 illustrates an example in which a publisher system2004 may contact each of N clusters (2006-1, . . . , 2006-N) to carryout an identification test transaction.

Various techniques may be used for selecting a suitable TDV cluster toimplement an identification test. In some embodiments, the publishersystem 2004 may select a TDV cluster randomly or based on any trafficand/or load information available to the publisher system 2004.

In some embodiments, the publisher system 2004 may query a DNS server2001 with a domain name and/or host name for the third-party system. TheDNS server 2001 may return an IP address for a specific TDV clusterchosen based on any number of suitable factors, such as traffic andgeography. For example, the DNS server 2001 may direct the publishersystem 2004 to a geographically closest TDV cluster.

In some embodiments, the third-party system may include a custom loadbalancer 2003. The publisher system 2004 may contact the load balancer2003, which may select a specific TDV cluster based on overall loadconditions and transmit a host name and/or IP address of the selectedTDV cluster to the publisher system 2004.

VII.D Advertisement Matching Service

As discussed above, information from one or more sponsoring entities maybe incorporated into challenge graphics in accordance with someembodiments. For example, some challenge graphics may be associated withone or more marketing campaigns and may incorporate campaign informationin one or more graphical or textual features, or in some other suitablemanner.

In some embodiments, a challenge graphic may be selected for a givenidentification test transaction at least in part by selecting amarketing campaign based on information regarding the transaction. Thismay be done to improve the effectiveness of the marketing campaigns, toguarantee a level of service to a sponsoring entity, and/or to achieveother suitable goals.

In some embodiments, an advertisement matching service (AMS) may be usedto select a marketing campaign for each identification test transaction.The AMS may be part of a system for implementing identification tests,or it may be external to the system.

In some embodiments, for example, as illustrated in FIG. 21A, an AMS2105 may be invoked by a token server 2107 of a third-party system aspart of a process for generating a token (e.g., act 1714 of FIG. 17).Upon receiving a token request via a token interface (e.g., from apublisher system or a user system), the token server 2107 may transmit acampaign request to the AMS 2105. The campaign request may include anysuitable information regarding the present identification testtransaction (e.g., any information included in the token request), tomake the information available to the AMS for use in selecting amarketing campaign. As an example, a campaign request may include anycombination of the following information.

-   -   1) PID: An identifier for a publisher who has requested the        present identification test transaction.    -   2) URI: A URI of a resource to which a user wishes to gain        access. For example, this may be a URI of a web page that a user        wishes to view.    -   3) IP: An IP address of a user to whom an identification test is        to be administered.

In some embodiments, the IP address of a user may be used as anindication of a geographic or logical location of the user (thus, theterm “location” when used herein is intended to encompass bothgeographical and logical location alternatives unless context indicatesotherwise). By examining IP addresses of users requesting challengegraphics for identification tests, a marketing campaign targeting ageographic area may be selected for those users whose IP addresses matchthe targeted geographical area. Additionally, or alternatively, aresource URI may be used as an indication of user interest. For example,if a user is attempting to view a web page related to vacationing, amarketing campaign for one or more travel destinations may be selected.As another example, if the web page indicates a particular destination,an airline campaign advertising air fairs relating to that destinationmay be selected. An IP address of a user may be used to provide evenmore focused advertising, such as advertising air fairs for travelingbetween the user's location as indicated by the IP address and a traveldestination as indicated by a web page that the user is attempting toview.

A marketing campaign selected by the AMS 2105 may be returned to thetoken server 2107 via a campaign response, which may include a campaignidentifier. The token server 2107 may use the campaign identifier toselect a specific challenge graphic, for example, by determining abucket identifier and an index into the bucket (as discussed above inconnection with FIG. 17). The challenge graphic may be selected in anysuitable way, for example, randomly within a campaign, or based on anysuitable information available to the token server 2107. A token maythen be generated accordingly and returned via the token interface.

It should be appreciated that the arrangements illustrated in FIG. 21Ais merely illustrative, as other arrangements may also be possible. Insome embodiments (e.g., as illustrated in FIG. 21B), the AMS 2105 may beused as an interface for obtaining tokens, instead of the token server2107. The AMS 2105 may receive a token request and use informationcontained therein to select a marketing campaign. Then the AMS 2105issues a modified/augmented token request to the token server 2107, withan identifier for the selected marketing campaign. The token server 2107may generate a token based on the campaign identifier and returns thetoken to the AMS 2105, which then forwards the token to an entity thathas requested the token via the token interface (e.g., a publishersystem or a user system).

VIII. Risk Assessment

In some conventional systems, identification tests are implemented inaddition to password-based access control methods to increase securityagainst bot attacks that guess passwords by brute force (i.e.,repeatedly submitting a randomly selected password until a correctpassword is selected by chance). For example, if a user fails to input acorrect combination of user name and password at a first attempt to login to a system, the user is required to pass an identification test at asubsequent log-in attempt.

The inventor has appreciated that conventional risk assessmentcapabilities such as those described above are limited in severalaspects. For example, the determination of risk is based on a verylimited amount of information about a user (e.g., that the user enteredan incorrect password at one attempt). Additionally, there is noaccumulation of historical information regarding a user (e.g., pastidentification results) and hence no adaptive implementation ofidentification tests based on historical information (e.g., pastidentification test results).

In some embodiments, a risk assessment system is provided for assessinga security risk associated with an electronic transaction based on anidentity of a user that takes part in the electronic transaction. Forexample, a level of security risk may be determined based on userinformation (e.g., results of past identification tests administered tothe user, results of past electronic transactions involving the user,etc.). Additionally, or alternatively, the level of security risk may bedetermined based on contextual information such as information regardingthe present electronic transaction.

In some embodiments, a risk assessment system is provided as part of athird-party system. This may enable the risk assessment system to accessand make use of any combination of information available to thethird-party system. Alternatively, the risk assessment system may beimplemented separately as a stand-alone system, and may obtaintransaction information from the third party system.

In some embodiments, a risk assessment system may perform riskassessment activities at the request of and/or in cooperation with apublisher system. For example, when a user requests access to one ormore resources of the publisher, the publisher system may request therisk assessment system to determine a level of security risk associatedwith the access request. The publisher system may provide to the riskassessment system any combination of information available to thepublisher to be used in determining the level of security risk.

In some embodiments, a result provided by a risk assessment systemregarding an electronic transaction may influence a manner in which theelectronic transaction proceeds. For example, a risk assessment resultmay be used to adjust a security parameter (e.g., a difficulty level) ofan identification test that is administered in connection with thepresent electronic transaction. However, it should be appreciated thataspects of the present disclosure relating to risk assessment are notlimited to the use of identification tests, as risk assessment may beperformed based on other available information. Non-limiting examples ofinformation that may be used to assess risk are discussed in greaterdetail below.

FIG. 22 outlines an illustrative method that may be performed by a riskassessment system to determine a security risk associated with anelectronic transaction. In act 2210, the risk assessment system mayreceive information regarding the electronic transaction. Thisinformation may be received from any suitable combination of sources,such as a third-party system for implementing identification tests, apublisher system, and/or a user system. Additionally, as discussed ingreater detail below, any suitable combination of information may bereceived in act 2210 to enable the risk assessment system to take intoaccount various aspects of the electronic transaction.

In act 2220, part or all of the information received in act 2210 may beprocessed immediately after act 2210. This may enable the riskassessment system to react to new information in a timely manner.Additionally, or alternatively, more in-depth processing may beperformed in act 2230 on part or all of the information received in act2210. The in-depth processing may take place immediately following act2210, or at some time after act 2210, for example, when sufficientprocessing resources become available.

In act 2240, processed data resulting from immediate processing (act2220) and/or in-depth processing (act 2230) may be stored in one or moredata storage locations. For example, processed data may be stored inassociation with a user identifier, such as an IP address of a user.This may enable the risk assessment system to retrieve all availableinformation regarding a user in determining a security risk associatedwith an electronic transaction involving the user.

In act 2250, some or all of the processed data may be retrieved andanalyzed. This may occur on an on-going basis (e.g., periodically),and/or on a per-query basis (e.g., when the risk assessment system isrequested to analyze a given electronic transaction). As a result of theanalysis, a risk score may be provided and/or updated. In someembodiments, the risk score may be associated with a user and mayindicate a level of trustworthiness of the user. Examples of varioustypes of analysis that may be performed in act 2250 are described ingreater detail below.

In act 2260, an up-to-date risk score may be provided to one or moredifferent entities. For example, the risk score may be provided to athird-party system for implementing identification tests, which may usethe risk score to determine a manner in which an identification test isimplemented. As another example, the risk score may be provided to apublisher, which may use the risk score to determine an access privilegeto be granted to a user. As with act 2250, act 2260 may occur on anon-going and/or per-query basis. Additionally, risk scores may beprovided in a batched fashion. For example, multiple scores associatedwith multiple users may be provided all at once.

It should be appreciated that the risk assessment method outlined inFIG. 22 is merely illustrative, as other methods may also be suitable.Additionally, a risk assessment method, such as that outlined in FIG.22, may be employed a number of different scenarios, some examples ofwhich are discussed below.

In some embodiments, a risk assessment system may determine a numericdegree of risk associated with an electronic transaction (as opposed toa binary “yes”/“no” prediction on whether the electronic transaction isdeemed to be risky). For instance, the risk assessment system may lookfor any risk factors and increase (or decrease) the degree of risk basedon the presence (or absence) of a risk factor. Risk factors with higherpredictive value (e.g., having a low rate of false positives and/or alow rate of false negatives when tested on known data) may lead tolarger increases/decreases in the degree of risk. As a non-limitingexample, an observation of user activity may be associated with a largerincrease in the degree of risk if it deviates from expected oracceptable user behavior to a greater extent. As another non-limitingexample, an observation of user activity may be associated with a largerincrease in the degree of risk if the activity more closely resembles anon-desirable behavior or is similar to other high risk activities. Itshould be appreciated that expected or acceptable behavior may bespecified based on one or more characteristics, where eachcharacteristic may have one or more expected or acceptable ranges. Thus,in some embodiments, an observation may lead to a decrease in the degreeof risk if one or more of its characteristics fall within the respectiveexpected or acceptable ranges. Similarly, an observation may lead to anincrease in the degree of risk if one or more of its characteristicsfall outside the respective expected or acceptable ranges.

In some embodiments, records may be maintained regarding one or morepast transactions. The records may be maintained in any suitable manner,for example, the last N transactions, the transactions from the last Ndays, etc., where N is any suitable number. Measurements may be takenfrom each recorded transaction. Examples of measurements include, butare not limited to, the time at which a transaction began, the durationof a transaction, the number of website pages loaded during thetransaction, etc. It should be appreciated that some measurements (e.g.,start time) may be taken directly from recorded data, while othermeasurements may be derived from multiple pieces of recorded data (e.g.,duration may be computed based on start time and end time).

As discussed above, user behavior may in some embodiments be analyzedacross multiple dimensions, for example, by obtaining and analyzingmeasurements with respect to different characteristics (e.g., duration,number of pages loaded, etc.). In some embodiments, a deterministic rulemay be applied to one or more of the measurements to assess risk. Forexample, a rule may check whether a transaction is completed faster thana selected threshold, where the threshold is indicative of how quickly ahuman can reasonably complete a transaction of the same type. A higherrisk may be flagged if the transaction duration is lower than thethreshold. In some embodiments, a statistical analysis (e.g., a logisticregression) may be performed on one or more of the measurements. As anon-limiting example, at least two pieces of information may becollected from a population of past transactions: time to complete atransaction and number of completed transactions in the last hour. Ifthe population generally (e.g., on average) completes a singletransaction in 30 seconds and two transactions per hour, then a User Awho completes five transactions in an hour each in less than 10 seconds,may be flagged as imposing a higher risk, or as being more anomalous,compared to a User B who completes five transactions in an hour each in30 seconds. Similarly, the User B may be flagged as imposing a higherrisk, or as being more anomalous, than a User C who completes twotransactions in an hour each in 29 seconds. However, it should beappreciated that a risk assessment system may track and analyze morethan two characteristics and/or characteristics different from the twodescribed above. Additionally, each characteristic may be used more thanonce, for example, as input to different analyses. In some embodiments,a risk assessment system may receive various logs and outputs from athird-party system that provides identification tests. The riskassessment system may examine one or more records of an identificationtest transaction to determine a user IP address associated with theidentification test transaction. Additionally, the risk assessmentsystem may determine whether the user passed or failed thatidentification test and use that information to update its assessment ofwhether the user IP address is likely to be associated with a human useror a bot.

The inventor has appreciated that many IP addresses may be shared bymultiple users, and it may be relatively easy for an attacker to changeIP addresses. Accordingly, in some embodiments, a risk assessment systemmay rely on past information to various degrees. For example, the riskassessment system may not simply blacklist or whitelist IP addresses.Rather, risk assessment may be performed on an on-going basis, based onboth past and present information.

In some embodiments, a risk assessment system may receive and analyzeidentification test information in real time. That is, the riskassessment system may receive and analyze information as anidentification test is being administered, rather than after theidentification test has concluded. This may enable quick feedback ofrisk information (e.g., within minutes or seconds after new informationbecomes available). For example, a risk assessment result may beprovided to a publisher as part of an identification test result, andmay take into account information such as how much time a user took tosubmit an identification test result and/or how many times a useractivated a refresh button to request a new challenge graphic.

In some embodiments, a risk assessment may be used by a plurality ofpublishers and may provide coordinated information updates. For example,if it is determined that one publisher is under attack, anotherpublisher may be alerted so that the other publisher may performsecurity upgrades accordingly.

In some embodiments, a risk assessment system may provide riskinformation to a third-party system for providing identification testsat various stages of the implementation of an identification test. Forexample, risk information may be provided prior to or during generationof a token (e.g., act 1714 of FIG. 17). Additionally, or alternatively,risk information may be provided prior to or during validation of a userresponse (e.g., act 1760 of FIG. 17).

In some embodiments, a risk assessment system may be implemented insettings other than identification tests. For example, a risk assessmentsystem may be used to evaluate a risk involved in a credit cardtransaction (e.g., to determine whether additional validation proceduresare to be performed following an initial validation procedure).Additionally, a honeypot (e.g., a link or an email address placed on awebpage in such a way that it is visible to bots but not to humans) maybe used to collect additional information for use by a risk assessmentsystem. Alternatively, or additionally, a risk assessment system may beused to determine whether a honey pot (or other suitable securityfeatures) is to be implemented.

In some embodiments, a risk assessment system may be implemented todetermine a level of risk associated with an account managementtransaction such as account creation, account access, informationrecovery, password reset, profile modification, etc. A risk assessmentmay also be performed to determine a level of risk associated with auser input, such as a user providing content via a contact form, commentform, or any other suitable types of input form. Further still, a riskassessment may be performed to determine a level of risk associated witha user accessing one or more resources, such as website data, pages on awebsite, linked website content (e.g. image content, style sheets,and/or program code such as JavaScript or Flash), etc. In someembodiments, a risk assessment system may take into account variousinformation regarding an electronic transaction in evaluating a securityrisk associated with the electronic transaction. For example, a riskassessment system may take into account a location and/or purpose of theelectronic transaction. For example, different types of electronictransactions such as random verification, account creation andinformation posting may have different characteristics and may triggerdifferent methods of risk analysis. For example, registering for a largenumber of email accounts in a day may result in a different riskassessment than posting a large number of messages on a message board ina day. As another example, posting on a blog or message board may takelonger than a random verification, because a user may need to compose apost prior to submitting a response.

In some embodiments, a risk assessment system may analyze informationassociated with a network address or identifier (e.g., IP address, hostname, MAC (Media Access Control) address, IMEI (International MobileStation Equipment Identity), etc., or an identifier derived at least inpart based on any suitable combination of the foregoing) involved in anelectronic transaction to evaluate security risk. For example, the riskassessment system may analyze information associated with a networkaddress or identifier that identifies one or more devices from which arequest is received to initiate the electronic transaction, or fromwhich one or more subsequent communications pertaining to the electronictransaction are received. As another example, the network address oridentifier may identify one or more devices to which one or morecommunications pertaining to the electronic transaction are transmitted.

Any suitable information or combination of information associated with anetwork address or identifier may be analyzed. For instance, in someembodiments, the risk assessment system may take into account geographicinformation associated with the network address or identifier. Examplesof geographic information include, but are not limited to city block,neighborhood, city, state, country, region, continent, etc. Any suitablegeographic division may be used, as aspects of the present disclosureare not limited in this regard. Furthermore, geographic information maybe obtained in any suitable manner. For example, in some embodiments, apublisher may pass geographic information to a risk assessment system(e.g., with a request for risk assessment and/or on a regular basis).Further still, the risk assessment system may use geographic informationfor any suitable purpose. For instance, geographic information may beused to determine one or more probabilities relating to usercharacteristics such as income, education, ethnicity, home ownership,age, number of dependents, work status, etc.

In some embodiments, the risk assessment system may take into accountnetwork information associated with a network address or identifier. Forexample, the risk assessment system may determine a connection type(e.g., cable, cellular, satellite, Wi-Fi, etc.) predominant to thenetwork address or identifier. This may be done by examining the networkaddress or identifier to identify certain patterns (e.g., networkprefixes) indicative of a connection type, or by observing connectioncharacteristics such as connection speed. Other methods for determiningconnection type may also be used, as aspects of the present disclosureare not so limited. As one example, the risk assessment system maydetermine whether a network is a shared network based on the number ofunique devices observed from the network (e.g., based on whether thatnumber exceeds a certain threshold). As another example, the riskassessment system may determine whether a network device is a proxy (oranonymous proxy) by examining the diversity of browser configurationsobserved from the device, such as different language settings.

As another example, the risk assessment system may take into account oneor more network functions associated with a network address oridentifier (e.g., Wi-Fi hotspot, proxy server, anonymous proxy server,etc.). As yet another example, the risk assessment system may analyzeinformation relating to a network path leading to the device or devicesidentified by the network address or identifier (e.g., by examiningreceived packets to identify any forwarding header information).

In some embodiments, the risk assessment system may analyze informationrelating to one or more resources that are accessed during an electronictransaction. For example, the risk assessment system may determinewhether the electronic transaction is performed using a mobile device ora desktop device by determining whether a resource accessed during theelectronic transaction is designed for mobile devices or desktopdevices. As another example, the risk assessment system may analyzewhich resource or combination of resources are accessed from a pluralityof available resources during the electronic transaction. For instance,the risk assessment system may analyze which content (e.g., images,program code, plugin content such as Flash content, etc.) is downloadedfrom a website. Such content may be analyzed by itself, or in thecontext of other contents available from the same web site. Furthermore,the risk assessment system may take into account whether a resourceaccessed during the electronic transaction is executed or otherwiseproperly decoded. Further still, the risk assessment system may takeinto account how resources are accessed, such as the order of accesses,the time between accesses, the quantity of synchronous or asynchronousaccesses, etc.

In some embodiments, the risk assessment system may analyze informationrelating to one or more software components used in an electronictransaction (e.g., web browser, media player, etc.). For instance, therisk assessment system may evaluate reported aspects or capabilities ofthe software components, such as language configuration, screenresolution, ability to store and/or retrieve certain types of dataelements (e.g., cookies), ability to execute program code (e.g., throughJavaScript), a listing of one or more extensions and/or plugins, etc.Additionally, or alternatively, the risk assessment system may evaluateprotocol header information provided by a software component, such asHTTP header information provided by a web browser, which may include anynumber of standard and/or customer header fields.

In some embodiments, the risk assessment system may determine whetherany reported aspect or capability (e.g., browser type, available pluginor extension, etc.) is accurate using independently obtainedinformation. For example, information may be obtained using JavaScriptor Flash in a web browser, or any other suitable program code. Such aprogram may be designed to obtain and report status directly orindirectly (e.g., by accessing an external resource). In someembodiments, such a program may be designed to convey information byfailing to affirmatively report status.

In some embodiments, the risk assessment system may determine whetherany reported aspect or capability is accurate by examining inputcontent. For example, if a browser reports a particular language setting(e.g., US English), the risk assessment system may examine input contentto determine whether it contains characters not with the reportedsetting (e.g., characters using an encoding other than US English).

In some embodiments, the risk assessment system may analyze one or moreactivities or patterns of activities observed during an electronictransaction. For instance, the risk assessment system may analyze one ormore aspects of how certain steps (e.g., web site page loads) areperformed during an electronic transaction. Examples of such aspectsinclude, but are not limited to, ordering of steps, presence of anyunexpected step, absence of any expected step, time between steps,completeness of a step (e.g., accessing of all associated resourcesand/or associated data measurements), and coherence of measured databetween steps (e.g., IP address, browser information, etc.). Forexample, in some embodiments, an expected access pattern may be a userperforming steps A, B, and C and accessing all associated resources in acommon manner, whereas atypical access patterns may include any one ormore of: performing only steps B and C, not accessing all resources,quicker than usual timing, change in IP address between steps, change inbrowser information between steps, etc. Observing any atypical accesspattern may indicate a higher level of risk.

Additionally, or alternatively, the risk assessment system may analyzeone or more aspects of how certain elements within a step are performedduring an electronic transaction. For example, a step may include one ormore web site input controls, and the risk assessment system may takeinto account how the website input controls are accessed and how thecorresponding input is applied. In some embodiments, the risk assessmentsystem may determine whether input elements are entered in an order thatcorresponds to a web page's visual layout, or to a defined HTML“tabindex.” The latter may suggest a lower or higher level of risk,depending on the circumstances. Other examples of input patterns thatmay be analyzed include, but are not limited to, user typographic orinput rate, time between key or input events, mouse movement, touchevent, number of key inputs relative to length of submitted inputcontent, etc.

In some embodiments, the risk assessment system may analyze contents ofinputs, in addition to, or instead of analyzing how the inputs areentered during an electronic transaction. For example, the riskassessment system may use one or more deterministic rules and/orstatistical models to determine whether one or more inputs should beflagged as being suspicious. An example of a deterministic rule maycheck whether an address entered in an address field is in geographicproximity to a location measured from an IP address associated with theelectronic transaction. An example of a statistical model may be aMarkov chain trained against an expected input set (e.g., a set of humannames) to determine whether a name entered by a user is likely to belegitimate.

In some embodiments, one or more objective criteria may be used toevaluate input content, such as whether a mailing address is valid,whether an email address is functional, etc. Alternatively, oradditionally, input content may be evaluated based on one or moreexperience-based criteria. For example, a recently created email addressmay be less reputable than one that has been active for a period oftime. Furthermore, a criterion may relate to only one or more parts ofan input. For example, only the domain name portion of an email addressmay be relevant in applying a criterion that indicates a higher level ofrisk based on whether a domain name has been recently established and/orhas an abnormally high number of transactions associated with it. Insome embodiments, such experience-based criteria may be learned fromtraining data derived from known instances of security attacks such asbot or human net attacks. Alternatively, or additionally,experience-based criteria may be determined from a suitable number ofrecent transactions.

Although various examples of information that may be analyzed by a riskassessment system are discussed above in detail, it should beappreciated that such examples are provided solely for purposes ofillustration. Aspects of the present disclosure are not limited to theuse of any particular information or combination of information inassessing a level of risk associate with an electronic transaction.Other types of information may also be used, such as historicalinformation accumulated over time and/or information from independentsources, as discussed in greater detail below.

In some embodiments, a risk assessment system may collect informationregarding multiple transactions over time. Risk assessment may beperformed on a cumulative basis, taking into account all previoustransactions associated with a user (e.g., as identified by a networkaddress or identifier such as an IP address). Alternatively, only someof the previous transactions may be taken into account, such as a movingwindow of N most recent transactions, where N is a configurable number.As yet another option, one or more suitable selection criteria may beused to select a subset of recent transactions. Non-limiting examples ofselection criteria include level of risk (e.g., below or above a certainthreshold), particular action or combination of actions taken, time ofday, etc.

The multiple transactions may be analyzed individually, collectively asa group, or in any other suitable manner. For example, the riskassessment system may analyze whether the transactions fall into aconsistent pattern over time, such as being performed at some detectablefrequency. Such a pattern may be generated by a bot that is programmedto evade IP volume filtering techniques by performing transactions at asufficiently low frequency. Nonetheless, the frequency pattern may bedetectable over a longer period of time (e.g., days, weeks, months,etc.).

In some embodiments, information obtained from one or more independentsources may be used to assess a level of risk associated with anelectronic transaction in addition to, or instead of, informationobtained from the electronic transaction itself. For example, where anelectronic transaction takes place via a sequence of communications(e.g., via a website), information obtained outside the sequence ofcommunications may be analyzed by the risk assessment system in additionto, or instead of, information obtained from the sequence ofcommunications. Such “out-of-stream” information may be obtained in anysuitable way, for example, by accessing a data warehouse or other typesof storage.

Non-limiting examples of out-of-stream information that may be used by arisk assessment system include user actions or events that take placebefore or during the electronic transaction. Such as the user making orreceiving a phone call (e.g., via the voice channel of a mobile phone orvia the data channel using a suitable protocol such as a Voice over IPprotocol), sending or receiving a message (e.g., via email, SMS, IM,etc.), installing, launching, or closing an application, taking anaction within an application or on a website, asking a question, givingan opinion, rating or reviewing a product, application, or service,changing account information such as email address, mailing address,billing address, shipping address, phone number, and/or other contactinformation, etc.

The information collected by a risk assessment system may be analyzed inany suitable way, as aspects of the present disclosure are not limitedto any particular analysis method or combination of analysis methods.For example, as discussed above, deterministic rules developed based onexpert knowledge may be used to identify patterns indicative of aheightened level of risk. As another example, statistical models builtand/or tuned using training data derived from known attacks may be usedto identify suspicious patterns and may additionally provide confidencescores indicative of likelihoods of attack.

The inventor has recognized and appreciated that certain patterns mayindicate a higher risk in the context of one group but not in thecontext of another group. In some embodiments, transactions may becategorized into different groups for evaluation to facilitate accuraterisk assessment by allowing different techniques to be applied based ongroup membership. For example, the time it takes an average user toinput information using a keyboard may be different from the time ittakes to input the same information using a touch pad on a mobiledevice. Thus, in some embodiments, transactions may be categorized intodifferent groups based on device type, and different thresholds forinput speed may be used depending on the particular group a transactionfalls into. Examples of other characteristics that may be used tocategorize transactions include, but are not limited to, geographiclocation (e.g., city, state, country, etc.), input language, connectionspeed, connection type, network function (e.g., anonymous proxy), devicetype, device version, software version, display screen resolution, inputmethod, etc. Any of these characteristics may be used, either alone orin combination with other characteristics, to categorize transactionsinto different groups.

In some embodiments, one or more characteristics may be sequenced tofurther categorize transactions into subgroups. As a non-limitingexample, transactions may be first categorized based on language intogroups, and then each group may be further categorized into subgroupsbased on device type. By categorizing the transactions into smallersubgroups, there may be more opportunities to detect patterns that areindicative of heighted risks within individual groups, where suchpatterns may not be visible when considering the transaction populationas a whole.

While various techniques to categorize transactions are discussed abovein detail, it should be appreciated that such techniques are providedmerely for purposes of illustration. Aspects of the present disclosureare not limited to the use of any particular categorization technique,nor to the use of categorization at all.

The inventor has further recognized and appreciated that an electronictransaction may have one or more identifying characteristics. Examplesof identifying characteristics include, but are not limited to, networkaddress or identifier (e.g., IP address, host name, etc.), accountidentifier, email address, physical address, web browser cookie, phonenumber, device identifier (e.g., a hardware device identification, suchas an IMEI number or MAC address, or a software device identification,which may be generated by hashing or otherwise combining any one or moreaspects of a device such as capabilities, available plugins,configuration parameters, software versions, etc.), or any othersuitable identifying value. It should be appreciated that an identifyingcharacteristic need not uniquely identify a user. Rather, in someembodiments, an identifying characteristic may merely provide someinformation as to the identity of a user involved in an electronictransaction, so that when two transactions share an identifyingcharacteristic, there is an increased likelihood that the same user isinvolved in both transactions.

In some embodiments, two or more identifying characteristics may beassociated with each other. For example, a particular account ID mayhave been previously detected as performing transactions from a list ofIP addresses and/or a list of device identifiers. In some embodiments,an identifying characteristic may be associated with informationrelating to transactions having that identifying characteristic. Forinstance, an IP address may be associated with information relating toone or more transactions performed from that IP address.

The inventor has recognized and appreciated that it may be beneficial tocreate and maintain transaction histories associated with at least someof the identifying characteristics. A transaction history associatedwith an identifying characteristic (e.g., IP address, user account ID,etc.) may allow ready retrieval of relevant information when analyzing anew transaction having that identifying characteristic (e.g., for riskassessment purposes).

Accordingly, in some embodiments, information associated with anidentifying characteristic may be stored in manner that allows theinformation to be retrieved using the identifying characteristic (e.g.,in a relational database). Examples of such information include, but arenot limited to, associated identifying characteristics (e.g., for crossreference), identifiers for associated transactions, session identifiersfor communication sessions associated with the transactions, time ofeach session or transaction, transaction scores, publisher reportedtransaction scores or results, purposes of transactions, specifictransaction details (such as a dollar amount for a financial transfertransaction, or an identifier for an event), etc. Other types ofinformation may also be stored, as aspects of the present disclosure isnot limited to the storage of any particular information or combinationof information associated with an identifying characteristic.Furthermore, the stored information may be obtained in any suitablemanner, such as in stream (e.g., from an electronic transaction itself,including any communication session that is part of the electronictransaction) or out of stream (e.g., outside the electronictransaction).

Information stored in association with an identifying characteristic maybe used in any suitable way, as aspects of the present disclosure arenot limited in this regard. In some embodiments, a newly detectedassociation between two or more identifying characteristics may indicatea higher level of risk. For example, as discussed above, a particularaccount ID may have been previously detected as performing transactionsfrom a list of IP addresses and/or a list of device identifiers. If anew transaction is detected involving that account ID but having an IPaddress that is not in the associated list of IP address and/or a deviceidentifier that is not in the associated list of device identifiers, anelevated risk assessment may be triggered.

In some embodiments, a change in a property of an identifyingcharacteristic may indicate a higher level of risk. For example, a usermay have been previously detected as performing transactions from a listof IP addresses, and all IP addresses in the list may be associated witha particular geographic region. If a new transaction is detected havinga different IP address that is from outside the associated geographicregion, a higher risk evaluation may be triggered. In some embodiments,a change in a property of an identifying characteristic may trigger ahigher risk evaluation only if it occurs in a suspicious manner. Forexample, user activity (e.g., performing a transaction or a step in atransaction) may be detected from a geographic location X and a device W(e.g., as determined based on IP address information relating to thedevice W), and sometime later further user activity may be detected froma geographic location Y and the same device W, but the locations X and Ymay be so distant that it is impossible or unlikely that the user hasmoved from X to Y in that amount of time. This may result in a higherrisk evaluation.

It should be appreciated that suspicious patterns may be identified inany suitable way, as aspects of the present disclosure are not limitedin that regard. For example, in some embodiments, candidate patterns maybe designed by experts and tested using data derived from known securityattacks to evaluate their ability to predict attacks. Alternatively, oradditionally, suspicious patterns may be automatically learned fromtraining data derived from known security attacks. Also, in someembodiments, multiple suspicious patterns may be used collectively, sothat no one pattern is determinative. For example, each pattern may beassociated with a weight and a risk score may be computed as a weightedsum over all relevant patterns (e.g., by adding a weight w, to the sumfor each i-th pattern that is observed).

In some embodiments, multiple risk categories may be specified, and adifferent risk score may be determined for each risk category (e.g.,based on different pieces of information and/or different techniques forevaluating information such as those discussed above). An overall risksignature may then be determined based on the category-specific riskscores. For example, in some embodiments, an electronic transaction maybe associated with an N-tuple of values, each value being a risk scorein a different risk category. If that N-tuple falls into a selected setof N-tuples, the electronic transaction may be assigned a risk signaturecorresponding to the selected set of N-tuples. For instance, theselected set may be specified based on M risk categories, where M may besmaller than N. Thus, not all of the category-specific risk scores inthe N-tuple may be relevant for the particular risk signature.

Furthermore, in some embodiments, the selected set may be specifiedbased on a range for each of the M relevant risk categories, so that anygiven N-tuple falls into the selected subset if the category-specificrisk score in each of the M risk categories falls into the respectiverange. As a non-limiting example, a signature may require at least oneof two categories to have a risk score greater than a particularthreshold to activate the signature. As another non-limiting example, asignature may require two categories from a grouping of three or morecategories to both have a risk score, or to have a combined risk score,that is greater than a particular threshold to activate the signature.One or more additional requirements may also be imposed, such asrequiring that a category from a different grouping of categories alsohave a risk score greater than a particular threshold to activate thesignature, where the second threshold may be the same as or differentfrom the first threshold. The assigned risk signature may be used in anysuitable manner, for example, to update an overall risk score (e.g., aweighted risk score as discussed above) and/or to compute a differentrisk score.

While various ways are described above for storing information and usingthe stored information to facilitate risk assessment, it should beappreciated that such descriptions are provided solely for purposes ofillustration. Other techniques of collecting, storing, and/or analyzinginformation may also be used to evaluate security risk, as aspects ofthe present disclosure are not limited to the use of any particulartechnique or combination of techniques.

As discussed above, a user may request that a correct response to anidentification test be sent in a text message. In some embodiments, arisk assessment system may monitor text message requests for behaviorsconsistent with nefarious activity. For example, the risk-assessmentsystem may monitor the frequency with which a text message is requestedfor a given phone number and take into account such information in arisk assessment analysis.

In some embodiments, various pieces of information (e.g., current userinformation, user address history and/or other risk factors) may becombined by a risk assessment system using different relativeweightings. The different relative weightings may change over time, andmay be determined based on inputs from an entity external to the riskassessment system (e.g., a publisher).

In some embodiments, a publisher may use risk information provided by arisk assessment system to determine security measures to be taken withrespect to a user. For example, a publisher may decide to deny a user'srequest to access one or more resources if the risk information indicatea high risk that the user is a bot, even if the user has correctlyresponded to an identification test. The denial may be temporary, andthe user may be given the opportunity to complete another identificationtest after a predetermined amount of time. Alternatively, oradditionally, a publisher may decide to impose more stringent securityrequirements on a high risk user, such as additional identificationtests (e.g., at different difficulty levels) as the user traversesdifferent portions of the publisher's web site. A publisher may evenemploy “silent” security measures, so that a high risk user is not awarethat its access request has been effectively denied. For example, apublisher may allow a high risk user to open a new email account, butmay silently filter out all outgoing emails sent from the newly openedaccount. This may prevent leakage of information to high risk users thatmay otherwise occur with direct denial of access.

In some embodiments, a risk assessment may result in no response fromthe risk assessment system, for example, because the outcome passes thereporting criterion or criteria specified by an entity requesting therisk assessment (e.g., a publisher). In other embodiments, a riskassessment may result in some information being reported, but noresponse is visible to the user, for example, because the transaction isflagged as suspicious but the risk assessment system is not sufficientlyconfident that the transaction is part of a security attack. If the riskassessment system is sufficiently confident, the risk assessment systemmay block the transaction or cause another entity to do so.

In some embodiments, a risk assessment may result in the user beingrequested to complete a subsequent task such as an identification test(e.g., a captcha, which may or may not be animated, a knowledge-basedquestion, an additional authentication such as answering a phone call ortaking an action on a device or in an application, etc.).

In some embodiments, a risk assessment may result in a transaction oraccount being flagged for further review. If the outcome of the riskassessment is sufficiently worrisome (e.g., as determined based on somesuitable criterion or criteria, which may be configurable), an accountmay become temporary disabled or limited.

Depending on the implementation, one or more different limitations orconstraints may be applied based on one or more aspects of a riskassessment outcome. For instance, in some embodiments, an entityimposing a limitation or restriction may take into account the specificbehavior observed and/or risk identified in determining how an accountis to be limited. For example, if a new email account is identified by arisk assessment system as potentially being created by a bot, actionscommonly abused by bots (e.g., sending many identical emails or othertypes of emails that are likely to be spams) may be limited, while otheractions may remain unconstrained. A limitation may be either permanentor temporarily, as aspects of the present disclosure are not limited inthat regard.

As discussed above, identifying characteristics (e.g., IP address,device identifier, etc.) may be associated with each other, for example,because they have been observed in one or more common transactions inthe past. In some embodiments, any limitation or restriction imposedwith respect to one identifying characteristic may be carried over toassociated identifying characteristics. For example, if a riskassessment leads to an account being disabled, an associated IP addressmay also be disabled.

While specific examples of responses to risk assessment outcomes aredescribed above, it should be appreciated that aspects of the presentdisclosure are not limited to any of these examples, as any suitableresponse or combination of responses may be invoked based on a riskassessment outcome. For example, various polices may be applied todetermine one or more responses, and the policies may beentity-specific, so that different entities may respond differently torisk.

In some embodiments, identification tests may be trackable. For example,each identification test administered may be associated with a uniqueidentifying tag. The identifying tag may be created by a publisher forwhom the identification test is administered. A risk assessment systemmay maintain a list of identifying tags for those identification testsin which a user provides a correct response but is later discovered tobe a bot or a “human net” (i.e., a collection of humans incentivized tosolve identification tests). This list of identifying tags may bereturned to the publisher upon request, or on an ongoing (e.g., regularor irregular) basis, to enable the publisher to take any necessarycorrective measures, such as suspending an account and/or redacting aposted comment.

In some embodiments, identification tests may be trackable usingidentifying tags that are recognizable by more than one publisher. Forexample, an IP address of a user to whom an identification test isadministered may be used as an identifying tag. The risk assessmentsystem may maintain a record associated with each identifying tag andmay provide some or all of the information contained in the record to apublisher or any other suitable party. The record may contain anycombination of information associated with each identifying tag, forexample, identification test results associated with the identifying tagand/or information indicating a purpose for each administeredidentification test (e.g., account creation or posting a comment).

FIG. 23 shows an illustrative implementation of a risk assessment system2300, comprising a log receiver 2392, a processing grid 2394, a datawarehouse 2396 and a risk server 2398. As shown in FIG. 23, the logreceiver 2392 may receive log information regarding an electronictransaction from any suitable combination of sources, such as athird-party system 2306 for implementing identification tests and/or apublisher system 2304 (cf. act 2210 of FIG. 22). The log information mayinclude information regarding an access request initiated by a user, anIP address of the user, information regarding a resource that the useris attempting to access, a response from the user during anidentification test, and/or a characteristic of the user's response(e.g., how quickly the user returned the response). Other combinationsof information may also be possible.

In some embodiments, the log receiver 2392 may distribute some or all ofthe received log information to the risk server 2398 for immediateprocessing (cf. act 2220 of FIG. 22). This information may betransmitted in near real time and at a relatively-high priority.Additionally, or alternatively, the log receiver 2392 may distributesome or all of the received log information to the processing grid 2394for in-depth processing (cf. act 2230 of FIG. 22). The log informationtransmitted to the processing grid 2394 may include more detailedinformation than the information transmitted directly to the risk server2398.

In some embodiments, the processing grid 2394 may be a conventional gridcomputer network that parses input logs from the log receiver 2392 andlooks for patterns. Many different numbers and types of questions may beasked during a search for patterns. Additionally, the number and/ortypes of questions may evolve over time. Below is an illustrative listof questions, although other may also be possible.

-   -   1) What is the last known activity from a given address?    -   2) Is there a correlation between a geographic location and bot        attacks?    -   3) Does time of day/week/month correlate to any bot-attack        information?    -   4) Is there a correlation between given hosting providers and        bot attacks?    -   5) Is there a correlation between a given network owner and bot        attacks?    -   6) Is a response to an identification test correct? If so, how        much time has elapsed before the user sends the response? If        not, is the response a putative typo? For example, is an        incorrect key located in proximity to a correct key on the        keyboard?

Log information processed by the processing grid 2394 and/or the riskserver 2398 may be stored in the data warehouse 2396 (cf. act 2240 ofFIG. 22), and may be subsequently retrieved and analyzed by the riskserver 2398 (cf. act 2250 of FIG. 22).

In some embodiments, the risk server 2398 may combine log informationfrom the log receiver 2392 with any previously-obtained and processedinformation associated with a user address of a user stored in the datawarehouse 2396. The combined information may be used to update a riskassessment associated with the user address. The risk server 2398 maythen provide the up-to-date risk assessment to the publisher system 2304and/or the third-party system 2306 (cf. act 2260 of FIG. 22).

Many different criteria and/or techniques may be used in updating a riskassessment. For example, a current risk assessment may be computed as aseries of events over time, taking into account an assumption that riskmay change according to recent behavior and may not be simply a staticview of history (e.g., many users may have dynamic addresses). Asanother example, an understanding of forwarded data and proxy serversmay be needed, such as understanding how America Online® accesses theInternet using proxy servers. Furthermore, attacks or probes from botsmay need to be detected quickly, while incorrect responses fromlegitimate users (i.e., false positive errors) may need to be detectedbut not penalized heavily. Also, to reduce the likelihood of falsepositive errors, a user may not be categorized as high risk simply basedon a small number of incorrect responses. Additional evidence may berequired to make such a categorization, such as the total number ofresponses submitted within a given time period and/or the time of day atwhich the responses are submitted, or the distribution or amount of timebetween responses (e.g., responses in sequence faster than a typicalhuman can act suggest responses from a bot).

Various inventive aspects described herein may be used with any computeror device having a processor that may be programmed to take any of theactions described above. FIG. 24 is a schematic illustration of anexemplary computer 2400 on which various inventive aspects may beimplemented. The computer 2400 includes a processor or processing unit2401 and a memory 2402 that may include volatile and/or non-volatilememory. The computer 2400 also includes storage 2405 (e.g., one or moredisk drives) in addition to the system memory 2402. The memory 2402 maystore one or more instructions to program the processing unit 2401 toperform any of the functions described herein. As mentioned above, thereference herein to a computer may include any device having aprogrammed processor, including a rack-mounted computer, a desktopcomputer, a laptop computer, a tablet computer or any of numerousdevices that may not generally be regarded as a computer, which includea programmed processor (e.g., a PDA, an MP3 Player, a mobile telephone,wireless headphones, etc.).

The computer may have one or more input and output devices, such asdevices 2406 and 2407 illustrated in FIG. 24. These devices may be used,among other things, to present a user interface. Examples of outputdevices that may be used to provide a user interface include printers ordisplay screens for visual presentation of output and speakers or othersound generating devices for audible presentation of output. Examples ofinput devices that can be used for a user interface include keyboards,and pointing devices, such as mice, touch pads, and digitizing tablets.As another example, a computer may receive input information throughspeech recognition or in other audible format.

Computer 2400 may also comprise one or more network interface cards(e.g., 2418) to enable communication via one or more networks (e.g.,2419). Examples of networks include a local area network or a wide areanetwork, such as an enterprise network or the Internet. Such networksmay be based on any suitable technology and may operate according to anysuitable protocol and may include wireless networks, wired networks orfiber optic networks.

The above-described embodiments may be implemented in any of numerousways. For example, the embodiments may be implemented using hardware,software or a combination thereof. When implemented in software, thesoftware code may be executed on any suitable processor or collection ofprocessors, whether provided in a single computer or distributed in amodular fashion among a number of different computers or processors.

Also, the various methods or processes outlined herein may be coded assoftware that is executable on one or more processors that employ anyone of a variety of operating systems or platforms. Additionally, suchsoftware may be written using any number of suitable programminglanguages and/or programming or scripting tools, and also may becompiled as executable machine language code or intermediate code thatis executed on a framework or virtual machine.

In this respect, various inventive aspects may be embodied as a computerreadable medium (or multiple computer readable media) (e.g., a computermemory, one or more floppy discs, compact discs, optical discs, magnetictapes, flash memories, circuit configurations in Field Programmable GateArrays or other semiconductor devices, or other tangible computerstorage medium) encoded with one or more programs that, when executed onone or more computers or other processors, perform methods thatimplement the various embodiments discussed above. The computer readablemedium or media may be transportable, such that the program or programsstored thereon may be loaded onto one or more different computers orother processors to implement various inventive aspects as discussedabove.

The terms “program” or “software” are used herein in a generic sense torefer to any type of computer code or set of computer-executableinstructions that may be employed to program a computer or otherprocessor to implement various inventive aspects as discussed above.Computer-executable instructions may be in many forms, such as programmodules, executed by one or more computers or other devices. Generally,program modules include routines, programs, objects, components, datastructures, etc., that perform particular tasks or implement particularabstract data types. Typically, the functionality of the program modulesmay be combined or distributed as desired in various embodiments.

Also, data structures may be stored in computer-readable media in anysuitable form. For simplicity of illustration, data structures may beshown to have fields that are related through location in the datastructure. Such relationships may likewise be achieved by assigningstorage for the fields with locations in a computer-readable medium thatconveys relationship between the fields. However, any suitable mechanismmay be used to establish a relationship between information in fields ofa data structure, including through the use of pointers, tags or othermechanisms that establish relationship between data elements.

Also, the invention may be embodied as a method, of which examples havebeen provided. The acts performed as part of the method may be orderedin any suitable way. Accordingly, embodiments may be constructed inwhich acts are performed in an order different than illustrated, whichmay include performing some acts simultaneously, even though shown assequential acts in illustrative embodiments.

Use of ordinal terms such as “first,” “second,” “third,” etc., in theclaims to modify a claim element does not by itself connote anypriority, precedence, or order of one claim element over another or thetemporal order in which acts of a method are performed, but are usedmerely as labels to distinguish one claim element having a certain namefrom another element having a same name (but for use of the ordinalterm) to distinguish the claim elements.

Also, the phraseology and terminology used herein is for the purpose ofdescription and should not be regarded as limiting. The use of“including,” “comprising,” or “having,” “containing,” “involving,” andvariations thereof herein, is meant to encompass the items listedthereafter and equivalents thereof as well as additional items. Thephrases “or” and “and/or” should be understood to mean “either or both”of the elements so conjoined, i.e., the elements that are conjunctivelypresent in some cases and disjunctively present in other cases.

Having thus described several inventive aspects of at least someembodiments, it is to be appreciated that various alterations,modifications, and improvements will readily occur to those skilled inthe art. Such alterations, modifications and improvements are intendedto be within the spirit and scope of the present disclosure.Accordingly, the foregoing description and drawings are by way ofexample only.

What is claimed is: 1-58. (canceled)
 59. A computer-implemented methodfor analyzing responses in animated identification tests, comprising:operating at least one first computer to monitor responses to aplurality of animated identification tests; associating each responsewith a same user identifier; measuring at least one characteristic ofthe responses to identify a pattern; and providing, based at least inpart on the identified pattern, score information in association withthe user identifier, the score information indicative of a level oftrustworthiness.
 60. The method of claim 59, further comprising: storingthe score information in association with the user identifier; receivinga request for an animated identification test; associating the requestfor an animated identification test with the user identifier; andoperating at least one second computer to provide an animatedidentification test based at least in part on the score informationstored in association with the user identifier.
 61. The method of claim59, wherein the at least one characteristic comprises an amount of timebetween delivering a challenge message and receiving a response to thechallenge message.
 62. The method of claim 59, wherein the responses areactual responses, and wherein the at least one characteristic comprisesa difference between an actual response and a correct response.
 63. Themethod of claim 59, further comprising: monitoring a rate at whichrequests for animated identification tests are received at the computer,the requests for animated identification tests being associated with theuser identifier.
 64. The method of claim 59, further comprising: at theat least one first computer, monitoring a time of day at which a requestfor an animated identification test is received, the request for ananimated identification test being associated with the user identifier.65. The method of claim 59, further comprising: determining, based atleast in part on the responses to the plurality of animatedidentification tests, that the user identifier is associated with a botattack; and providing an updated assessment regarding at least one ofthe plurality of animated identification test, the updated assessmentbeing different from an earlier assessment given to the at least one ofthe plurality of animated identification test.
 66. The method of claim59, wherein the score information comprises information indicative of apurpose of at least one of the plurality of animated identificationtests.
 67. At least one computer-readable medium encoded with aplurality of instructions that, when executed by at least one processor,perform a method for analyzing responses in animated identificationtests, the method comprising: operating at least one first computer tomonitor responses to a plurality of animated identification tests;associating each response with a same user identifier; measuring atleast one characteristic of the responses to identify a pattern; andproviding, based at least in part on the identified pattern, scoreinformation in association with the user identifier, the scoreinformation indicative of a level of trustworthiness.
 68. A computersystem for analyzing responses in animated identification tests,comprising at least one processor programmed to: monitor responses to aplurality of animated identification tests; associate each response witha same user identifier; measure at least one characteristic of theresponses to identify a pattern; and provide, based at least in part onthe identified pattern, score information in association with the useridentifier, the score information indicative of a level oftrustworthiness.
 69. The computer system of claim 68, wherein the atleast one processor is further programmed to: store the scoreinformation in association with the user identifier; receive a requestfor an animated identification test; associate the request for ananimated identification test with the user identifier; and provide ananimated identification test based at least in part on the scoreinformation stored in association with the user identifier.
 70. Thecomputer system of claim 69, wherein the at least one processor isprogrammed to provide an animated identification test at least in partby determining a difficulty category based at least in part on the scoreinformation stored in association with the user identifier and selectinga challenge message in the difficulty category.
 71. The computer systemof claim 69, wherein the at least one processor is further programmed tomodify, based at least in part on a response to the challenge message,the scored information stored in association with the user identifier.72. The computer system of claim 68, wherein the at least onecharacteristic comprises an amount of time between delivering achallenge message and receiving a response to the challenge message. 73.The computer system of claim 68, wherein the responses are actualresponses, and wherein the at least one characteristic comprises adifference between an actual response and a correct response.
 74. Thecomputer system of claim 73, wherein the actual response comprises afirst character string and the correct response comprises a secondcharacter string, and wherein the at least one processor is programmedto measure at least one characteristic of the responses at least in partby determining a different between the first and second characterstrings.
 75. The computer system of claim 68, wherein the at least oneprocessor is further programmed to monitor a rate at which requests foranimated identification tests are received at the computer, the requestsfor animated identification tests being associated with the useridentifier.
 76. The computer system of claim 68, wherein the at leastone processor is further programmed to monitor a time of day at which arequest for an animated identification test is received, the request foran animated identification test being associated with the useridentifier.
 77. The computer system of claim 68, wherein the at leastone processor is further programmed to: determine, based at least inpart on the responses to the plurality of animated identification tests,that the user identifier is associated with a bot attack; and provide anupdated assessment regarding at least one of the plurality of animatedidentification test, the updated assessment being different from anearlier assessment given to the at least one of the plurality ofanimated identification test.
 78. The computer system of claim 68,wherein the score information comprises information indicative of apurpose of at least one of the plurality of animated identificationtests. 79-99. (canceled)